{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# treatment\n",
    "\n",
    "The treatment table allows users to document, in a structured format, specific active treatments for the patient. The treatment table can only be populated directly into eCareManager as structured text. Absence of a treatment documented in this table should not be used as evidence a specific treatment was not administered. Data includes patient treatment information such as when the treatment occurred, whether the treatment was active upon patient discharge, and the path of the treatment."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/alistairewj/.local/lib/python3.5/site-packages/psycopg2/__init__.py:144: UserWarning: The psycopg2 wheel package will be renamed from release 2.8; in order to keep installing from binary please use \"pip install psycopg2-binary\" instead. For details see: <http://initd.org/psycopg/docs/install.html#binary-install-from-pypi>.\n",
      "  \"\"\")\n"
     ]
    }
   ],
   "source": [
    "# Import libraries\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import psycopg2\n",
    "import getpass\n",
    "import pdvega\n",
    "\n",
    "# for configuring connection \n",
    "from configobj import ConfigObj\n",
    "import os\n",
    "\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Database: eicu\n",
      "Username: alistairewj\n"
     ]
    }
   ],
   "source": [
    "# Create a database connection using settings from config file\n",
    "config='../db/config.ini'\n",
    "\n",
    "# connection info\n",
    "conn_info = dict()\n",
    "if os.path.isfile(config):\n",
    "    config = ConfigObj(config)\n",
    "    conn_info[\"sqluser\"] = config['username']\n",
    "    conn_info[\"sqlpass\"] = config['password']\n",
    "    conn_info[\"sqlhost\"] = config['host']\n",
    "    conn_info[\"sqlport\"] = config['port']\n",
    "    conn_info[\"dbname\"] = config['dbname']\n",
    "    conn_info[\"schema_name\"] = config['schema_name']\n",
    "else:\n",
    "    conn_info[\"sqluser\"] = 'postgres'\n",
    "    conn_info[\"sqlpass\"] = ''\n",
    "    conn_info[\"sqlhost\"] = 'localhost'\n",
    "    conn_info[\"sqlport\"] = 5432\n",
    "    conn_info[\"dbname\"] = 'eicu'\n",
    "    conn_info[\"schema_name\"] = 'public,eicu_crd'\n",
    "    \n",
    "# Connect to the eICU database\n",
    "print('Database: {}'.format(conn_info['dbname']))\n",
    "print('Username: {}'.format(conn_info[\"sqluser\"]))\n",
    "if conn_info[\"sqlpass\"] == '':\n",
    "    # try connecting without password, i.e. peer or OS authentication\n",
    "    try:\n",
    "        if (conn_info[\"sqlhost\"] == 'localhost') & (conn_info[\"sqlport\"]=='5432'):\n",
    "            con = psycopg2.connect(dbname=conn_info[\"dbname\"],\n",
    "                                   user=conn_info[\"sqluser\"])            \n",
    "        else:\n",
    "            con = psycopg2.connect(dbname=conn_info[\"dbname\"],\n",
    "                                   host=conn_info[\"sqlhost\"],\n",
    "                                   port=conn_info[\"sqlport\"],\n",
    "                                   user=conn_info[\"sqluser\"])\n",
    "    except:\n",
    "        conn_info[\"sqlpass\"] = getpass.getpass('Password: ')\n",
    "\n",
    "        con = psycopg2.connect(dbname=conn_info[\"dbname\"],\n",
    "                               host=conn_info[\"sqlhost\"],\n",
    "                               port=conn_info[\"sqlport\"],\n",
    "                               user=conn_info[\"sqluser\"],\n",
    "                               password=conn_info[\"sqlpass\"])\n",
    "query_schema = 'set search_path to ' + conn_info['schema_name'] + ';'"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Examine a single patient"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "patientunitstayid = 242040"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>patientunitstayid</th>\n",
       "      <th>treatmentid</th>\n",
       "      <th>treatmentyear</th>\n",
       "      <th>treatmenttime24</th>\n",
       "      <th>treatmenttime</th>\n",
       "      <th>treatmentoffset</th>\n",
       "      <th>treatmentstring</th>\n",
       "      <th>activeupondischarge</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>242040</td>\n",
       "      <td>9472063</td>\n",
       "      <td>2014</td>\n",
       "      <td>20:41:55</td>\n",
       "      <td>night</td>\n",
       "      <td>198</td>\n",
       "      <td>infectious diseases|medications|therapeutic an...</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>242040</td>\n",
       "      <td>10207446</td>\n",
       "      <td>2014</td>\n",
       "      <td>20:41:55</td>\n",
       "      <td>night</td>\n",
       "      <td>198</td>\n",
       "      <td>cardiovascular|consultations|Cardiology consul...</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>242040</td>\n",
       "      <td>9164625</td>\n",
       "      <td>2014</td>\n",
       "      <td>20:41:55</td>\n",
       "      <td>night</td>\n",
       "      <td>198</td>\n",
       "      <td>cardiovascular|non-operative procedures|diagno...</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>242040</td>\n",
       "      <td>8399138</td>\n",
       "      <td>2014</td>\n",
       "      <td>20:41:55</td>\n",
       "      <td>night</td>\n",
       "      <td>198</td>\n",
       "      <td>cardiovascular|hypertension|angiotensin II rec...</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>242040</td>\n",
       "      <td>9784345</td>\n",
       "      <td>2014</td>\n",
       "      <td>20:41:55</td>\n",
       "      <td>night</td>\n",
       "      <td>198</td>\n",
       "      <td>endocrine|glucose metabolism|insulin</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   patientunitstayid  treatmentid  treatmentyear treatmenttime24  \\\n",
       "0             242040      9472063           2014        20:41:55   \n",
       "1             242040     10207446           2014        20:41:55   \n",
       "2             242040      9164625           2014        20:41:55   \n",
       "3             242040      8399138           2014        20:41:55   \n",
       "4             242040      9784345           2014        20:41:55   \n",
       "\n",
       "  treatmenttime  treatmentoffset  \\\n",
       "0         night              198   \n",
       "1         night              198   \n",
       "2         night              198   \n",
       "3         night              198   \n",
       "4         night              198   \n",
       "\n",
       "                                     treatmentstring activeupondischarge  \n",
       "0  infectious diseases|medications|therapeutic an...               False  \n",
       "1  cardiovascular|consultations|Cardiology consul...               False  \n",
       "2  cardiovascular|non-operative procedures|diagno...               False  \n",
       "3  cardiovascular|hypertension|angiotensin II rec...               False  \n",
       "4               endocrine|glucose metabolism|insulin               False  "
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "query = query_schema + \"\"\"\n",
    "select *\n",
    "from treatment\n",
    "where patientunitstayid = {}\n",
    "order by treatmentoffset\n",
    "\"\"\".format(patientunitstayid)\n",
    "\n",
    "df = pd.read_sql_query(query, con)\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
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7nwDckpPmH4C5Zrajme0EjHb33/tB6jsB35K0U04ad3mcp5jZzmXy9TKwj5ntApxHrSXy\nJJLlrpenPTgbyMzu9fwdZ2a9zGy+3/rA8349cFZBXmC0mfUF9gMuk9TZ7+0KHGlm3wIWAId7+P2A\nywsKCrA1cJ2ZbQt8SqqDpZQqe0nrAYcD23s+LihTFgV6AQOAHYEBkjZVmop9CenM3l5AH0mHmdk5\nwHwvg+M8/JYu6/bAorxw7q8zMMH9PQn8sShPqwN3A6d5HfYH5lOX3DKT1Ac4AtgZOJD0MqLAjaR2\n0ZtUR9dl7nUH9gZ+QFJsAc4Bxnoer8gpr86k+t0e+IxUxt8hlfv5Of6L2QTY08zOzLmXJ88PSWVZ\nKJPLMgrrLsDppP66BbCXpA7ANaR21hu4GbgwTxBJJym9PJrw/vvvVyB6EATBystXc+a0WNwxRTkI\ngqB5mU5SBC4BHjKzsRWEGZ5R4vYGrgIwsxmSprn77qQH62dcL1sdeC4Tx92Z65uAEySdSVKm+uak\n2R84pvDDzD72y6MlnUT6f+juaRZkuBtA0jrAOmb2lLvfTlJ0iukK3CppS8CADpm0byhMGzazj3LC\n5nGff08kKSIABwCHFCyIQEdgM79+LBO3gIsk7QssATYGNvB7b5jZM359B3AqkLXGlir7uSQl8B9u\nQVzGipjDKDObCyDpReAbwHrAGDN7390HA/sC9+eEf93MCq/E+5QJt4TaNnEHtWVXYGtgjpmNBzCz\nT3PSKlVmewEPmNkCYIGkBz39tYA9gSG17w5YIxPf/T6l+kVJG1AZC6l9STQd+NLMFkmaTnpJUh9D\nykzZz5Nnb+BOD/OupCdJ5fwpMM7M3gSQNMXT/wTYAXjM89weyH1qM7MbSS8AqKqqsgpkD4IgWGlZ\nrXvLTXYJBTcIgqAZMbNXJO0KfB+4QNIoMzsf+IraWTMdi4J9XkHUIilsx5a4n41jKMliNxqYaGYf\nViK7pM1JVrc+Zvax0kZJWVkrkTPLn4EnzOxwST2AMQ0MX8yX/r2Y2v8vAUeY2aysR0m7UVfe44Bu\nQG9XkGZTm7diZaP4d8myl9QX+DZpne1/k6ypleShOB+V0tA6KNAYhapcmeXRDvjEzHqVuJ/Nu0r4\nKWaRmRVkX1KIw8yWSKqk7MqVV0Plyas7ATPNbI8KwgdBEKxSdNpj9/xpyu3a8fUzTm+xdGOKchAE\nQTPi002/MLM7gMtI02QBZuPTjUnTO0vxDHC0x7UdaSorwPOkKZHf9HudJW2VF4Fb1h4hTeXNm54M\n8Bh1185+DVibpBDMdYtWnlUWM/sE+ETS3u50XJ4/kgX3Lb+uLkr75wUFRdK6OWE/A7rkuBfzCGlt\nbmE95C5lZHnPFbX9SJbTAptJKigoPwKeLgqbW/ZusexqZg8DZ5CmtTaGcaTp4OtLag8cS5pWDLDI\np8E2NFw7aje3ysvTLKC7TzdGUpcchbFUmT0DHCypo5fBD2CpFfg1SUd5nJJUX5lUWs/Li7GkqePt\nldYt70sq51LMAroV2o+kDpK2Xw5yBkEQtHl63HILnfbYvY6bVl+djS65uMU2mIKw4AZBEDQ3O5LW\n7S0hrZH8hbv/iTSV9c+Ut2ReR5rW+yJpDetM0lrZ95WO+LlTUmHa57nAKyXiGUxap/hoifsXAH9T\n2gBpMfAnM7tP0mRP9w2SIlOKE4CbJVmZNC71vJwLjMi43wRsBUyTtAgYCBQf7TIIuEHSfKCcdezP\nwJUeVzvgNVzhKmIw8KBPbZ1AymOBWcAvJd0MvEh6MbCUMmX/GfCApI4kS17eOs96MbM5SsfXPOHx\njDCzB/z2jZ63SaT1xpWG+xzo62X/HmmqejbsQqUNlK5R2sRrPmnq+LyMt9wyM7PxkoaTpq6/S5o6\nPNfDHAdc7+l2AO4CppbJ/jRgsdJmZYNKrMNdngwjtbepJKv3b8zsHflmWcV4OR4JXC2pK+m56kpS\nvw2CIFjl6XFLqffsLYdqZ/4EQRAErY1b4jqY2QJJPYHHga3NbGED4zmLZF38Q8atBphtZoOaUeQV\nGp86/ZBvCNZccfYDqs2surnibIQM88xsrRaMfy0zm6e04/RTwElmtsxu3Y2Me7aZ9WiOuNoqVVVV\nNmFCc5ymFQRBsGogaaJvglkvYcENgiBoW6wJPOHTUgX8VyOU22FAT+pfDxoEjeVGn0LfEbi1uZTb\nIAiCIGgqoeAGQRC0IczsM+oeu9KYOA4vcWsMadfXwDGz2aRdcJuT2eTvgLzcaEnrrcf/oxaMvuUO\nRwyCIAhWekLBDYIgWEUwszGtLcOqgCvNs1tZjBUWMwsFNwiCIGg0sYtyEARBEARBEARBsFIQCm4Q\nBEEQBEEQBEGwUhAKbhC0MJLGSKry64clrdPaMhUjabak9RsYpsaPTmkVJPWT9FAzxlfjOw8j6XxJ\n/Zsr7kwaDS7nEvH0kzTIr1+VtHXR/SslnS1pin/mSZrl17d5+LmZ+1NaIr9l5K+WVHwsUH1h5tXv\nKzfcRpLurcfPGN9Nuc3hdbVn5vfJko5v5jR6+HFReWk3Wx+rUJZ66ysnzOm+m3Phd6PaSltnxKsj\nOODeA9jp1p044N4DGPHqiPoDBUEQtDInPnIiO96649JP79t7t/j4FWtwg6AZkbSamX1V6r6ZfX95\nytNS+FE2KxT11U0WMztveaZXJo72Zra4Hm93AceQztnFz4I9EtjLzC5xtzHAWWY2wX/3A8aaWd55\nsQ2Vscn5bEnM7G1Seayo9COdTfssgJnd0KrStCDelhpTX6cDdwBfNJMMba49j3h1BDXP1rBg8QIA\n5nw+h5pnawA4aIuDWlGyIAiC0pz4yIk8/87zddwWLlnI78b+Dmi58SssuEGQg6TjJU2TNFXS7e52\nsKQXJE2W9LikDdy9RtLtkp4BbpfUSdJdkl7y41o6ZeJdasGTdKakGf453d0ulvTLjP8aSWdJWkvS\nKEmTJE2XdKjf7yxphMs5Q9IAd+8j6Vl3HyepS7HVTNJDrugU5/1+SRMlzZR0UsZ9nqTLJU0F9si4\nt/N8rZNx+5ekDcqU2bcylsPJkrq4+9mev6mSLna3rAV8fUmzc2TuK+k5j+vZgkXT8zxc0mhgVE64\n30t6RdLTwNYZ90GSjszUyYveHv7ibj0kjXa3UZI2y4S7QdILwKWS1pP0qJflTaRjfwpp/IfXzRRJ\nfy+8NCgu57z0i7gTGJD5vS/wupm9nuO3QbgsV7j8oyR1c/cxSlbiCcBpFZTHBC/nrEK9kaSR3lYu\ndf8/lXRlJv0TJV1RJFOpvtDH0+/o/WKmpB2UsU5K2j5T5tMkbZmT5296W53qafRU4jKlPjZdtf2s\nn5fFvZJeljTY/X5P0pBMnEstoZIO8LY6SdIQSWu5+2xJf8rkaxslq/LJwBku8z6qO9Ogl6TnPS/D\nJH0tUz+XeF5fkbSPu/eQNNbTmKSMZbgMaxXnz+PqLelJpbHiEUndM2lf5fLOkNTX3Svqo0X1VS3p\nvuJ2UlRfpwIbkY7WeiLjfqHX4fOqHXe6SRoqabx/9nL34jE8t5y8Hp9SGnNnKbXtdqqg3TaVqyZd\ntVS5LbBg8QKumnRVcyYTBEHQrBQrtwWWsKRFx69QcIOgCEnbA+cC+5vZzsBpfutpYHcz24VkNftN\nJth2QH8zOxb4BfCFmW0L/BHonZNGb+AEYDdgd+BESbsAdwNHZ7we7W4LgMPNbFdgP+Byf9D8HvC2\nme1sZjsAIyWt7mFOc/n7A/MbUAQ/NbPepKNqTpW0nrt3Bl7wtJ4ueDazJcADwOGet91ICta7Zcrs\nLOCXZtYL2AeYL+lA4FBgN5d7mYfZMrwM7OPpnAdclLm3K3CkmX0rG8Dr4BigF/B9oE9xpJ73w4Ht\nzWwn4AK/dQ3p7M+dgMHA1ZlgmwB7mtmZpPp/2sy2B4YBBcVvW5JSupeXwWLgOA+/tJyBl0qkvxQz\nmw4skbSzOx1DUnrrYx/VnaLcM8dPZ2CCy/+k56fA6mZWZWaX11MePYC+wEHADZI6unsvL4MdgQGS\nNgXuAQ5WOgMYUh+5uUim3L5gZuOB4aQyuhS4w8yKp92eDFzlZV4FvJmT58HA37z89wTmAD90eQv9\n6bKCQgfsQrIgbgdsAewFPA7sJqmz+xkA3KX0cutc0lixKzABODOT9gfufj3J4j4buAG4wsx6mdnY\nIllvA872cp9O3fpZzcz6umwF9/eA73gaA6hbT6VYJn9eP9eQ+lVvUh1dmAmzppfxf1Fbfw3uo05e\nO1mKmV0NvA3sZ2b7uXNn4Hmvw6eAE939KlJZ9gGOAG7KRJUdw8uVU1/gFPffk9Q2Kmm3SDpJ6WXP\nhPfffz8nq6V55/N3GuQeBEHQ1mnJ8SumKAfBsuwPDDGzDwDM7CN33wS42x9sVwdey4QZbmYFJXJf\n/IHIzKZJmpaTxt7AMDP7HEDSfaSHv6slfV3SRkA34GMze8MfnC6StC+wBNgY2ID0UHu5pEuAh8xs\nrKQdgTn+wI+ZfeppVJr/UyUVzlHdFNgS+JCkhA0tEeZu0kPrLSQF6253L1VmzwB/lTQYuM/M3lRa\nA3qLmX3hcn9E5XQFblWyyBnQIXPvsRJx7UOqgy8AJA3P8TOXpFD9Q8kCV1iPuAfpwRbgduoq40My\n04r3LfgzsxGSPnb3b5NefIz3eulEeqiGuuVcKv1i7gSOkTQTOIy6ik4pKpmivITaurwDuC9z7+7M\ndbnyuMdfgvxL0qvANu4+yszmAkh6EfiGt/XRwA8kvQR0cAU+i8jvC+8A5wPjSWV2ak5+ngN+L2kT\nUrv7V52I00yCjc1sGICZLXD3vYE7vV7flfQk6YXIp8A4M3vT/U0BepjZ05JGkpSee0nK/W+Ab5EU\no2e83ld3mQoUyndipjxzkdQVWMfMnnSnW4EhGS/ZuHr4dQfgWkmFlypblUvDWSZ/pLOUdwAe83y0\nJ70IKHAngJk9JWltpdkdXWh4H4WcdgK8UY/MC6ntKxOB7/h1f2C7zFi4ttyCTt0xvFw5jTOzV12e\nO4G9zezeCtotZnYjcCNAVVWV1ZOHOmzYeUPmfD4n1z0IgmBFpCXHr7DgBkHlXANca2Y7Aj8HOmbu\nfd6M6QwhrUEbQK0ScRxJ4e3tlpF3gY5m9grJ+jEduEBSubWjX1G3z3cs9qA0Zbk/sIdbPyZn/C0o\nsx70OeCbSlNYD6P24Tq3zMzsYuBnJMXuGUnbLBtlrtzLyOz8GXjCrdgH00x142vx+gL3Aj8ARlYQ\nrJL0RLJ49vLP1mZW4/eWlnMD0r+LZO3vD0xz63lLkH0or7Rcix/kC7+/zLgtpvaF601ANckKdktO\nfLl9we+tB6xFUqaWaStm9k/gENKMhocl7V9hHspRKh+FOtmfZAX/jFTvj2XqfTsz+8+cuLLxNFWu\nbFxnkMprZ5IFe/UGxJONS8DMTD52NLMDMv7y6ryxfbRU+ZZjkZkVZMiGaUeaUVKQe2MzK2xIlZWh\nXDmVas/1tdsmcdqup9Gxfd0m3bF9R07b9bQSIYIgCFqf3TfcPde9He1adPwKBTcIlmU0cFRhaq6k\ndd29K/CWX/+kTPingB952B2AnXL8jAUOk7SmT2M83N0gKbXHkJTcgkWmK/CemS2StB/JioFber8w\nszuAy0jK7iygu6Q+7qeLpNWA2UAvXzO2KUlxKqYryWr8hSud+SNTEf4wOQz4K/CSmX2YiW+ZMpPU\n08ymW9oEaTzJqvcYcIJ8N9RMuc+mdpp3qc1nsulUVyIzqZ4OU1oz3YX00F0Ht+50NbOHSQ+9hWnA\nz5LqCJLCVTx1NJtGoS0cCHzN3UcBR0r6ut9bV9I3GpB+Hczs38AHwMVUNj25UgobVuH5eLqEv3Ll\ncZS3uZ6kKa6zyiVoZi+QZg78iPy85PYF5+/AH0jTjC8pDihpC+BVn9b6AEV905XQNyUd5v7X8PY4\nljQ9tr2/xNkXGFcuH6Qp3buSpsfe5W7Pk6b4ftPj7yypPivqZySFvQ5u1fxYvr4W+LGnWY6upNkd\nS9x/YzeLmwV0k7QHgKQOvrSjQGGN8t7AXJe1MX20UnLLKIdHSdOLcfl6lfBXrpz6StpcaTO3AXif\nqKDdNomDtjiImj1r6N65O0J079ydmj1rYoOpIAjaNAO/O3AZJXf1dqtz0T4Xtej4FVOUg6AIM5sp\n6ULgSUmLSVbMaqAGGOLTTEcDm5eI4nrgFp+q9hJpilxxGpOUjnkpPCTfZGaTM+l3Ad4ys8KctMHA\ng5Kmk9btvezuO5LWAy4BFgE+Ei4AAAAgAElEQVS/MLOFSpvgXCOpE8la1Z80Lfg14EWXa1KO7COB\nk132WaQH8kq5m6SsVmfcasgvs9NdOVkCzAT+x8y+9AfOCZIWAg8DvwP+AtyjtOFVqX3lLyVNfzy3\njJ86eB3cDUwlTQ8en+OtC/CA0rpRUbte8hRSHf8aeJ9ktcnjT8CdPnX4WeD/PO0XXdZH/UF5EfBL\noHhjqFLp53EnScG9r4yfLPv4lNMCF5hZ8fEsn5Me6M8lldEA8ilXHv9HaudrAyeb2YIKpsvfA/Qy\ns49z7uX2BaWjcxaZ2T+VNux61i20r2bCHg38WNIi0pTmi1iWHwN/l3Q+qV6OIr282YPUVgz4jZm9\nU27mgZkt9mnl1fjLHTN7X+lorTslreFezwVeKVMWDwL3Km2mdUrRvZ+Q1jWv6fks1Q4LXAcM9bIa\nSSNnN/gYcyRwtU+VXg24ktSXARZImkya6vtTd2twH20AN5L2H3g7sw43j1OBvyktG1mN9ALq5Bx/\n5cppPHAt8E3gCVLbKFCu3TaZg7Y4KBTaIAhWOAZ+d+ByT1O1s3iCIAgqR1INMNvMBrWyKKscPpW8\n2syqWzideWa2Vv0+S4YfRFob3tBzTR8ibQa0zM7XLYHSMUrVljZ1CpqAio6kWpnwfndWqbXrDWm3\nVVVVNmHCSldEQRAELYakiWZWVYnfmKIcBEEQtAkkrSPpFWD+8lJug6CpRLsNgiBoW8QU5SAIGssY\n0m6qwfJnNnB/SyfSFOuth69uoP9PqGxn3+ZmENGWmwUz69faMrQUZjaGNO4Vu7dWuw2CIAhyCAU3\nCIJG4Q97QSvgU2lnt7IYKw0xzT4IgiAIVh5iinIQBEEQBEEQBEGwUhAKbhAEQRAEQRAEQbBSsEIo\nuJLGSKry64clrdPaMhUjabak9RsYpsaPjFghkDTIj4ZA0k2StqvH/9J6K3KvN2xOmH6+Q2WzI+nZ\nRoQ5R9JxRW6HSDqngrCXSZop6bKGppsT1+mFc2P9d6P7h6Rq3xm5WWWR1EPSjMbG20hZlraXSupF\nUpWkq0vca3DfbmgarUVOnQ3ynWIL49NZRf6XloUkk3RH5t5qkt7P9lNJ35M0TtLLkqZIulvSZiVk\n2VDSXZL+LWmit5961zV6Hhb4cTXNhveHa5sQdqPmlKco/o0k1bsztaR5JdxP9iNwyo3TS/uNpMMa\nOmZ7uH6+k3Y5P+tI+q+Gxt1cFPeBSv211WeRIAiCoA2uwZW0mpl9Veq+mX1/ecrTUiid09hmqaAe\nftbYuJsStiUwsz0bEey7pDM1s/EMB4ZXEPYkYF0zW1xJQvXUxenAHcAXLkNr9o9cWZb3Q6CkOuNa\nJfXiR5q06JkdyyONRlCnzhrI58AOkjqZ2XzgO8BbhZuSdgCuAQ4xs5fc7RCgB34ecMavSOeJ3mpm\nx7jbzsAGlD8jFuBY0tmkPwRuKeexvnGtGakGZgBvt0TkZvY2cGQTwt9QgZ9svzkMeIh0hnZFFPfD\nMqwD/Bfp7NmK427Geqy0D7T+WDvtHhh1Psx9E7puAt8+D3Y6uv5wQRAErcmth8BrT9b+br8GHHpt\ni45fLWbBlXS8pGmSpkq63d0OlvSCpMmSHpe0gbvXSLpd0jPA7ZI6+Zv8lyQNAzpl4s1aEM6UNMM/\np7vbxZJ+mfFfI+ksSWtJGiVpkqTpkg71+50ljXA5Z0ga4O59JD3r7uMkdSl+oy/poYK1oyjv97sF\nYqakkzLu8yRdLmkqsEdRmBpJt0oaK+l1ST+UdKnLOlJSB0n7S7o/E+Y7Xj5IOtb9zpB0ScbP9zzP\nUyWNcre+kp7zenhW0tbuXi1puKTRwCglrpU0S9LjwNcz8Wat6tdLmuD5/VMFbWOMkjWrvZLFaIbL\nfobf/6a3j6kue08Pupake5WsQYP9oRhJvSU96WX+iKTumXSucNle8jq9T9K/JF2QrRf/zm0jOfKv\nDaxuZu8XuS9tH56vq718X1Wt5Xs4sBYwUdIAVd4n2kv6i5fVNEmnSDoV2Ah4QtITHq6+/tHDy2Kg\n19ejkjpRhPsb62UxSdKe7t7Py7VOPdQnC9C+OE1JPSVNyqS5ZeG3hy20/3GSvunu3SQNlTTeP3vl\nlVc99XKDt4lXJP0gk6+CxXc9l3GmpJsAZeL6D5dniqS/y19UKfXtgmX+caU+Nsbr/pCcNNaSdIvn\nb5qkI3Lq4DzP4wxJN0pL23sfDzPF05zh7u3993i///OG1lkjeBg4yK+PBe7M3DsbuKig3EJSmszs\nqZx49gMWZRUvM5tqZmNd1stUO04MyJRRT1J/OtfTXwbP/1ilvveiu5WqxxO8XYwD9srEMUjeh/33\nvMz12S7XVKX/nyOBKmCwx9+pTF2eKulFr6+73K2zpJtdvsnKGYeUmRXh7fs+pf+Jf0m6tMjvhS7b\n86o7vmSt8z92WWdI6puJ91qlvn8IcJn76Smpl8c3TdIwSV/zMGMkXSlpAnBakRylxteLgZ6Z9pxb\n38X1qGb4r8/rA8r5Pyvhb7ak9VXhmNpkpt0DD54Kc98ALH0/eGpyD4IgaKsUK7cAi7+EYT9v2fHL\nzJr9A2xPeuu+vv9e17+/BsivfwZc7tc1wESgk/8+E7jZr3cCvgKq/PdsYH2gNzAd6Ex6wJkJ7OKf\nJzOyvAhsSrJWr+1u6wP/S3pwPQIYmPHfFVgdeBXo425re/hq4NqM34eAflm5ivLbifQWfz3/bcDR\nmfA1QHXm+mmgA7Az6S3xgX5vGOkNuoCXgW7u/k/gYNIf7/8B3VzO0e6/G/AGsHmRXGsDq/l1f2Co\nX1cDb2b8/RB4DGjvaXwCHOn3xmTqpOC/vbvvVOynqH2MIT0A9gYey7iv498vAIf7dUdgTaAfMBfY\nhPRi5jlgby+vZzNlMoDatjMGuMSvTyNZU7oDa3g+C/Uyz79z20iO/D8Ezs9xr8bbB+nYkSEu63bA\n/2b8zctcV9onfgHcm6m3QpnPxttdhf2jB6k/9XL/9wD/kZG/xq/XBDr69ZbABL/OrYd6ZCmX5hMZ\n94uAUzJhf+/XxwMPZdp8Ib3NgJdKlFe/TJjiehnpsm9Jagcdi/xfDZzn1weR+u36wLbAg0AHv3cd\ncHymb2f766PU9uUpOTJdAlyZbQc57WndzPXtwMF+PQPYw68vBmb49UnAuX69BslavHkD62wQtWNa\nDckiOyXzWUjtODePND7f62U4pSiPk4CdK/zPOBW4osS9I6gdhzYgjXXd/d7vgT94vl4HNsgJ349k\nbS6Mg7n1SBobCuPo6sAz1G03Rxb3YeBA0vizZlG/HENm7CtTl28DaxSNfxdR2z/WIf2Xdi7KU49M\nvVeT/q+6ej28DmyaaZeFtC7NtI8a4KyMrAP9et+ieEvlfxrwLb8+H2/LHtd1RWU/qNz4ms1LufrO\nqccm/9eX6AOl/s+K/c2mnvGt3Kd3797WIP66vdkf117289ftGxZPEATB8iRv3Grk+IU/i1byaakp\nyvsDQ8zsAwAz+8jdNwHuVrKwrQ68lgkz3NI0N0h/sld72GmSpuWksTcwzMw+B5B0H7CPmV0t6etK\n65+6AR+b2RuSOgAXSdoXWAJsTPrznA5crmT1fMiSxWBHYI6ZjXcZPvU0Ks3/qZIO9+tNSQ/SHwKL\ngaFlwv2PmS2SNJ305zrS3acDPczMlKzh/yHpFpIV+HjSQ/gYc4uipMFehouBp8zsNc9HoR66ArdK\n2pL0ANQhI8NjGX/7Andamkr7tpJlN4+jlSzVq5EeRLYjPQDVx6vAFpKuAUYAj0rqAmxsZsNc5gWe\nJ4BxZvam/55CerD4BNgBeMz9tAfmZNIoTLGbDsw0szke/lVS3XyY8Svy28g7RXJ/j3qmQjr3m9kS\nkrVhgxJ+Ku0T/YEbzKflZeqoFLn9g1Qer5nZFPc3kVSOxXQArpXUi9SOsmsh8+rh6XrkKZXmTcAJ\nks4kvZzomwlzZ+b7Cr/uD2yX6YtrSyqc1Zotr3Lc4/XyL28H2xTd35f0EgMzGyHpY3f/NunFwXhP\nvxPwnt9bSN3++mWmLxfymqU/cEzhh5l9nONnP0m/Ib1sWBeYKWks0MXMnnM//wR+4NcHADup1tLY\nlTT2LKRxdQZJ6fxL4Yek2dmbPj73IFlPHy4ViaT1gFGelxuzcVbA3tSOQ+9KehLoQ2rLx5Jehi2R\nNBQ4CshbNzuuMA5Suh53o+44ejf1n23aH7jFzArTVkv1y2XqkqRkTyNZeu+n9lzjA4BDMhbWjvjL\nnDJyjDKzuS73i8A3SC83F5JexELqd98pEf5Ol/8pSWurzLICpbXO65hZ4ZX8raSXeQXuLhWU/PG1\nmFL1/SmZejSzyU39ry8hZ2P+zyoZU/F4TwLYbLPcpeilmftmw9yDIAjaOi04fi3vNbjXAH81s+FK\nU3trMvc+b8Z0hpDWJ21I7Z/tcaQ/wd7+4DmbZKF6RdKuwPeBC5Sm8Q4rEe9X1J3W3bHYg+erP8nC\n8oWkMRl/C6z8ussvAfxhbZG/rYD0J12oq1tID0YLSC8RvmqA4l3gz8ATZna4P5yOydxrUD1I2hw4\ni2Tt/lhpQ5FlyiUP978zaT3ryaQ1raeVCfJl5noxqUxEUlz3yA+yNMySovDZMi2Q20Zy4uxLsqjW\nRza9UpW0vPpEKbkWk1kCkOEM4F2SBbIdqb2VCl/JOFIqzaHAH0mzDiaaWfaFg+VctwN2L7z4KOB9\noNLysnp+l0KkNaK/zblX3F+zfbnB46ykjiTLYpU/tNdQf78SyQL+SFFc/WhcnVXKcOAvJAvbehn3\nmcCuwFSv116utK0laVPSOAZwg/tt0JpSfxG5JbUvtwoviPIU3GzbyK1HSYeVSW7p2C+pnadVqZzl\n6vIg0guVg4Hfe54EHGFmsypNg9L1m22X5eq9sX0ij1L9sNLxtSFxN+m/3szOz0bWhP+zSsZUzOxG\n4EaAqqqqhpVx1018enKOexAEwYpIC45fLbUGdzRwlL+1R9K67t6V2k1IflIm/FPAjzzsDqRpcMWM\nBQ6TtKakzsDh7gbpj+4Y0h9f4c1yV+A9/8Pbj/SGG3/7+4WZ3QFcRnogmwV0l9TH/XTxh9TZpIe0\ndv6AlrU2kUnnY1dutwF2L5PPBmNpc5G3SWvOClbEccC3fD1Qe5JV40ngeWBf/9MuVQ/VZZJ7Chig\ntLavO2mdXDFrkx465rqV8sBK86K0PrOdmQ31/OxqZp8BbxYeNiWtofI7XM4Cuknaw/13kLR9pTIU\nkdtGimTeHni5nhcVDU2zkj7xGPDzgrKUqcvPgC45/sv1j0rlmuOWzh+TLOP1UUqWkrii+ghwPcta\nxQdkvgsWy0eBUwoe3MLcUI7yPtwT2ILUhrJkx58DSdPIIVkgj5T0db+3rqRl2kiFPAZk1w9+reh+\n4aH6A7dQHwlgZp8An0naze8fkwnzCPALt2AhaSuv+3I0uM5yuBn4k5lNL3K/lKS0bZtxWxPAzN4w\ns17+uYH0n7GG6u5ZsJOkfUjttjAOdSMphONI41yNmfXwz0bARhXUSal6fIE0jq7nZXhUJsxsktUX\n0nrUwqyXx0gzENYsxOXu2XLNrUtXlDc1sydI65W7kpYTPAKcIi1dp7tLPflpDgrrXPcG5haswRmW\n5sfvfex1A2l8KFpglUup8bW4DZaq7zya+l9fnH65/7Pm6CuN59vnQYcivblDp+QeBEHQVtn8W/nu\natei41eLWHDNbKakC4EnJS0GJuPr+4AhSlP+RpPWh+VxPXCLpJdI07Im5qQxyd+uFv74bjKzyZn0\nuwBvFaakAoOBB5WmDE4grWUF2JG0ecYSYBHwCzNbqLSxxTVKm0XMJ1llnyFZCF50uZZukJNhJHCy\nyz6LpGQ2N4NJa05fAjCzOUrHOTxBevs/wswegKVTou7zh6n3SFPULiVNUT6XNDW4FMNI081fJK2D\neq7Yg5lNlTSZVJ5vkMqoUjYm1XPhRUvBovJj4O+SzifVyVF5gT39hUpTMq9Wmjq3GnAlySLUUEq1\nkSwHUjsVtTmoobI+cRNpuuQ0SYuAgSRL1Y3ASElvm9nSFxCl+odb7CvhOmCo0lEiI6nMOporSwUM\nJingjxa5f01pecKX1G4gdCrwN3dfjaSMntyAtCC15XGkh9mTzWyB6s6C+BNwp6SZpPWV/wdgZi96\nn3nU2+wikpL6egPTB7jA8zGDZPH5E3Bf4aaZfSJpIGm97TukXYIL/Ccw0MesJ0nrayG1kR7AJFeO\n3ietxS9HY+tsKT71eZnjj8xsuqTTgNuUNmb7gFSWf8zxa0rLOq6UdDZpxsBs0s61T5OWY0wlWRZ/\nY2bvSDqGZI3LMoyk8FxCCUrVo5k9r2RdfY609GFKJthA4AGlDQKX9gczG+kvWSZIWkiapv070prV\nGyTNd9nz6rI9cIePWwKu9nr/M2kMm+byvUbtNPSWYoGP4x2An+bcv4vU5k4lKZM/IeVvTdJSkxMq\nSCN3fDWzDyU9433hf4DfkF/fxUsJmvxf7+51+kCZ/7Mm95UmUdhtNHZRDoJgReInw1tlF+XC5jZB\nK+APU7PNbFADw10LTDazf7SEXEFpJD1G2lhoTr2eVzCUzmTuYWY1yznds0gbvvwh4zabNKXzg2ZO\naxBp/V29Z4i2VSStZWaFnb/PIW24VG5qf0PiHkTaFGhMc8QXrNooTY+vNrPqVhalzVFVVWUTJrS1\nU8OCIAjaLpImmtky57bn0ebOwQ3KI2kiyXrwq9aWZVXEzEpt0hI0AqVjrnqSZgoElXGQpN+Sxu/X\nKb/MIAiCIAiCYJWipILrD54lzbtm9sMWkWjVYgxpKlzFmFnv+n0FQaOYQpoWutwws8NLuPdoofSq\nWyLe5YmZ3U3pnWqbyv0s5zYQrNTMpnZ36CAIgiBYLpSz4BZ2ojyUdAbqYP99LGmTo6CJxDTAoC2R\nOeYiWEUxs1BGgmbDzGYTL0yCIAiC5UxJBdfMRgFIuiQ731npvL5SOxoGQRAEQRAEQRAEQatQyTFB\naxXtvLoZ6SiDIAiCIAiCIAiCIGgzVLLJ1K+AsZJmkY4y+Ca12+sHQRAEQRAEQRAEQZugXguumY0g\nnb95Nul8um3M7OGWFiwIVjYkjZFU5dcPS1qntWUqRtJsSes3MEyNHzHUlHR7+DmYDQlzup/DWfg9\nr4kyNKpOJFX7kV+NTbc4H01uG9m2VqH/fpL2zPwe5OdLNzb9k/0M5YaGG+RHy5Tz06R6LhNvtR/B\nVmjTZ2VkanRZZOLvIelHmd9VkpY5P7gRcbbpfuNta1BT0sjEdYgfjdWQMC3SXlqD+ye/xV4Xj2bz\nc0aw18WjuX/yW60tUhAEQb0cN/A5epwzYuln63P/p8XHr3oVXEmdgNOAE81sIrCxpANbVKogWMGR\nVHZ2hJl938watIN2W0RS+0aEWa3c7wZwOrBmvb4qpBXrpE4+GipHcR00pk6AfsCe9XmqFDO7wcxu\na674VhJ6AEsVXDObYGanVho4+g2Y2XAzu7il4leikqVby537J7/Fb++bzlufzMeAtz6Zz2/vmx5K\nbhAEbZrjBj7HM//+qI7bl18t4cx7prTo+FXJQH6z+9vbf78NXNRiEgVBG0LS8ZKmSZoq6XZ3O1jS\nC5ImS3pc0gbuXiPpdknPALdL6iTpLkkv+bFbnTLxLrWUSjpT0gz/nO5uF0v6ZcZ/jaSzJK0laZSk\nSZKmSzrU73eWNMLlnCFpgLv3kfSsu4+T1CVrqXI/D+VZzSTdL2mipJmSTsq4z5N0uaSpwB5FYfpK\nes7L5llJW7t7taThkkYDo9yqM1bScOBFD95e0kBP71Evv56SJmXi39Lzfippd/cnJD2RuX+h5/X5\nTL0MknS9u73qad/s9TKoRJ0sk3dJ7T2uGV72Z+SUWQ/P1yT/7Onu/ZSsqvdKelnSYH+YXiYf9cmR\nVwce5hIvq6Pc21Fe569I2sfDPSWpVyaepyXtDJwMnCFpSsEvsK/X4atyC6bn40lJD7j7xZKO83Sm\nS+rp/rIW0G8q9ZOpXiY9JXV3WaZ4eRbSzJblBpKGebipyliY/X5D+8LFkl5U6s9/KU6voUg6UdJ4\nT2eo3CrqbeTq4rIDLgb28Tyf4WX5kIdZWfrNMuNlhXXWQ6lfDPL2OlhSf0nPSPqXpL6Z8rg2E2a0\npzdK0mbuvrmX5XRJF1SY9ixJtwEzgE0lHet+Zki6JBPHvBJl1c3bwHj/7NWw1lQ/lz0yi/mLFtdx\nm79oMZc9Mqu5kwqCIGg2ipXbAkuMFh2/KlFwtzSzi4BFAGb2BWktbhCs1EjaHjgX2N/MdibNZAB4\nGtjdzHYB7iJN3S+wHdDfzI4lrVX/wsy2Bf4ILHOGsaTewAnAbsDuwImSdiGdc3p0xuvR7rYAONzM\ndgX2Ay6XJOB7wNtmtrOZ7QCMlLS6hznN5e8PzG9AEfzUz12uAk6VtJ67dwZe8LSeLgrzMrCPl815\n1H0ZtitwpJl9K/P7NDPbyn9vCfzNzLYnnQ99hJn9G5irWqXsBOAWM7ua9LJtPzPbLyPX857Xp4AT\nM2l/jaSMnwEMB64Atgd2zMRdX957ARub2Q5mtiNwS06494DveP0MALJTUHchWc+2A7YA9iqRj/rk\nKOS1uA4+NLNdzewu/72amfX1NP/obv8AqgEkbQV0NLOpwA3AFWbWy8zGut/upBebPyApZwUKCvG2\nwI+BrTydm4BTcvIwmFSvO5OsxHNIlsxHzKyXx5d3RNXVwJMebldgZtH9hvSF9YDDge3NbCfgAprO\nfWbWx+V7CfjPzL28sjsHGOtlfEVRXCt8vykzXmYpVWeQ9ve4HNjGPz/yMjwL+F1OXNcAt3p9Dqa2\nr10FXO99dE6FaW8JXOdluAi4BNif1Of7SDqsnrK6itR/+gBHkPrCMkg6SdIESRPef//9PC8lefuT\n/KG7lHsQBEFbpyXHr0oU3IWSOgIG6e0osLDFJAqCtsP+wBAz+wDAzAqvoTYBHpE0Hfg16YGvwHAz\nK/TYfYE7POw0YFpOGnsDw8zsczObB9xHetCdDHxd0kZKFraPzewN0suliyRNAx4HNgY2AKYD31Gy\n4u1jZnOBrYE5ZjbeZfjUzL5qQP5PVbIQPg9sSnoIBFgMDC0RpiswRGldYOFhuMBjmTIEGGdmr2V+\nv5Y5i3ciaUonpIfFE5Sm3g4A/lki7YXAQznhAR40MyOV07tmNt3MlpCUpqy/Anl5fxXYQtI1kr4H\nfJoTrgMw0NvGEJIym83vm57ulBLpViIH5NfB3UW/7/PvbFkMAX4gqQPwU2BQmbTvN7MlZvYiqY0V\nGG9mc8zsS+DfwKPuPr04T5K6kF4KDAMwswX+knQ8qU5rgB3N7LOc9PcHrvdwi71N14meyvvCXJKC\n8w9JPwS+KJPvStlByZo6HTiOum29VNmVYmXoN6XGyyyl6qyQj2z8ozJpF6cFSfEu5Ol2ameZ7QXc\nmXGvJO3Xzex5v+4DjDGz9328HEway6F0WfUHrpU0hfQiYG1Jy5w2YWY3mlmVmVV169YtJ0ul2Wid\nTg1yD4IgaOu05PhViYJ7PjAS2ETSrcATwG9bTKIgaPtcA1zrFoKfAx0z9z5vxnSGAEeSHk4Lystx\nQDegt1u/3iVZ4V4hWXamAxdIOq9MvF9Rt+93LPagNGW5P7CHWysmZ/wtMLPFxWGcPwNPuOXsYMqX\nTfHvLzPXi6nd5X0ocCDJGjbRzD4skfYifyAuDp+Ne0lROkuK/JXMu5l9TLI2jiFZMPOsNGeQ6mRn\nktV19Qryl0sj6qBUeS5Ny5XLx4BDSbMCBpcRISuvSrhny3OZsiyFmT1FUhreAgapERtS0YC+4IpK\nX+BeUjsa2Yj0ihkE/LePA3+iblsvVXalWOH7TYXk1llOPhrVrjJYjlu5tCsdt0uVVTvSrJ5e/tnY\nX1g2G7/+7tZ06lB3eX2nDu359Xe3bs5kgiAImpW9eq6b695OtOj4VckuyiNJa7pOBIYBfc1sVItJ\nFARth9GkdYzrAUgq9NKupAdzgJ+UCf8UvqmMpB2AnXL8jAUOk7SmpM6kaZSFKaJ3A8eQlNwhmbTf\nM7NFkvYDvuHxb0SaDn0HcBnpAX8W0F1SH/fTRWljmtlAL0ntJG1KevAvpivJavyFpG1I06crIVs2\n1RWGKYuZLQAeIVnzstOCPwO6NEcaReTmXWmdYTszG0qairlribBz3Ar1Y6CSDZ9K5aOxdVAfN5Gm\nc453pb2cDE3CLbNvFqZ4SlrD2/o3SBbBgS5PXlmOwo+kU1r/3LXofsV9wa1pXS2dAHAG6QVEU+kC\nzHFr+HEV+C9XxitDvyk1XmbJrbNG8ixpfIRU/oVx85ki94amPQ74lqT13fp9LPBkPbI8SmZ6foll\nD03isF025v/9cEc2XqcTAjZepxP/74c7ctguGzd3UkEQBM3G4BP3WEbJXWO1dvz16F4tOn6VfCsq\nqfhhvDAlakNJG/qUyyBYaTGzmZIuBJ6UtJhkQasGakjTCT8mPdRtXiKK64FbJL1EWqM3MSeNSUob\ntoxzp5t8enIh/S7AW2ZWWEs2GHjQp0VOIK3dA9gRuEzSEtIasl+Y2UKlDXauUdoNfT7JIvgMqT+/\n6HIt3Ywmw0jgZJd9FmmKbCVcCtwq6VxgRIVhKmEwSfl/NON2I2l95duWv361sZTK+8ak+iy8GMyb\nyXIdMNQtkiOpzDJUKh+NrYOymNlESZ9SV+l5ELhXaeOdvHW0TeHHwN8lnU9qm0cB+wC/lrQImAfk\nWXBPA26U9J8ka9kvgOcy9yvuCySF7gFfbiPgzGbI1x+AF4D3/bs+pXEasNinnA8ijScFVvh+U2a8\nLJYnr84awymk/vhrUh2c4O6nAf+UdDbwQEPTNrM5SkcRPUFqKyPM7IE8vxlOBf7m059XI73cPLlx\n2SrNYbtsHAptEAQrHINP3KN+T82MamfbFN2QCm9D1yBtjjKTNNhvD0yytKlIEASrOL6OcraZDWrB\nNM4iWeD+0FJpNBalM+Trl4IAACAASURBVIB7mFlNK4tSEW7hHEM603xJK4tTB3/ZM8jMxrSyKCsF\nbaHf+FT7ajOrbi0Z2iJVVVU2YcKE1hYjCIJghUHSRDOrqsRvSQuumRWOlbgXOKmwiYVvePP75hA0\nCIKgPpSOWOpJ2sQmaAJuWb4QOLOtKbdB8xL9JgiCIFhVqWTjhm0zOzRiZlOVjgMIgiCAZA38pKUi\nN7PDWyruZmIKaV1zm8fMbgNua205ynA/K0hZtnXaUL+ZTarXIAiCIFguVKLgzpR0A37cCWnThuLz\nCIMgWEVZ1aeTZl8ABk3DzEIRWskws9nES4sgCIJgOVLJMUE/IZ11eLZ/XqX8zrFBEARBEARBEARB\nsNyp14JrZvNJRy1c1vLiBEEQBEEQBEEQBEHjKGnBlXSnf0+WNKn4s/xEDIIVF0nVkq5tbTnKIamH\npDEtEG+179hb+H2TpO38erafK1su/O+Kfj/b3DI2BkmDJB3Z2nI0heYsW0k1vpN0myenTdbbDlsL\nSfdK2qIJ4Y+QZJKqMm6/lfS/kmZJ+q67dZP0tKQZhfOK3f2BorL6i6T9M7+XW717Wmctj7QqRdKY\nbNkuD4a+8xFVz86k+xNTqHp2JkPf+Wh5Jh8EQdAojpr8LzZ8YsrSzzfG/H/2zjtOi+r6/+8PiICK\nYCF2xY6ogLBoLBhQoykaJWKLDTUaE7s/jSZGxdhLYmIPtjWKiaJgw46iiIosHcXyjWI0omIBC4oI\n5/fHPcPOPsw8z7PLPruL3vfr9bx25s4t55aZnTPn3HunVPz5VcyCe7r/XaZf5CKRCEhazsy+beJi\nBwHTgfcAzOzX9Uz/R+Ci5MTMdmg0ySLf17YdRGpMLg2VvKd8IcfWZvZmkTitgA5mNjfjWgfCfrDj\nUmHdgAMJW/2tDTwpaTPgIOAGYDjwMHCfpL2ASWaWbqergRsJe39Hmph73/+E0157h68Wha0d352/\ngNNeeweAfddctTlFi0QikVz2m/QGY+Z8WSdsvhknzPgvULnnV64F18ze9cOfA1+Y2X/Sv4pIE4m0\nYNzS+aqkoZJmuIVlBb+22BIkqSrLIuqWv+slvSjpTUn9JN3ieVWn4h0kaZpbVC5NhX8h6UJJUzyP\nNTx8L0nj3NviyVT4YEm3SxoL3C7pWUk9U/k959t+pWW8RNJxqfPFlhNJp0saL2mqpPNSbTJD0o2S\nXpb0uKT2buGsAoZKmuxhmRYPSfdJmuDpj0nkANp72qFJ/f2vJF3u7TNN0gEe3s/LuCfVT8oo72iv\nxxRJ96b6sFrSVZKe9/4ZmCrvGrd6PQn8IGd89PR+mSpphKRVJC3nZfXzOBd7H+4i6b5U2h8rbOuC\npKMkvS7pJW/Xazy8s8s73n87pvroFq/7m5JObMa2XdXLnOpt0d3D/y7pHD/ew8diR0lvSWrj4Ssn\n55L6eB6TE3k8Tms/T8bhb8qVTxlj0i+doOCZNE1SV4+7orfpSwr31d4ePkjSA5KeAkZJWknSqFT6\nJF7ms6JYvxdwMHB/zjjbQGHv6deAnbLiAOcDlwJfp8L2Bv5tZvPN7C3g/4BtgQXACoQ97xdKWg44\nGbgsnaGZvQ2sJmnNDJnqOwZbK9xvyTg7xcMz7808JK2hcK9N8d8OeWV6eN4zNO/e7yfpoVT6a5Rh\ntVZ4rtd4eecVk7mhXPzmrMXKbcJXi4yL35xVieIikUikUShUbhMWQUWfX+UsMtUZeEbS05KOVQt1\n54pEmojNgevMbAvgM+B39Uy/CrA9cArwAHAlwaKytYKCtDbhxXQXoCfQR7VugysCL5pZD+BZ4GgP\nfw74oZltA/wb+H2qvG7AbmZ2EHAzwYKFguWmnZlNKZDvLmD/1Pn+wF2Sdgc2JbwQ9wR6S9rZ42wK\nXGtmWxK2C9rXzO4BaoCDzaynz+XP40gz601QPk6UtJqZnQl85WkPLoj/S5ehB7AbcLmktfzaNoSX\n827ARsCOGeUNN7M+3o4zgKNS19YiKA17Apd42ABCv3cDDgPyrJ3/BM4ws+7ANOBct/ANAq6XtBvw\nE+A84Gmgq6TOnvYI4Bbv/7OBH7rsXVP5/x240sz6APsCN6WudQX2IPTPuYnSSNO37XkEy193gpU4\n2ZLoD8ABkvoDVwFHuOVxNOEjKgTr4nAzWwDcCvzGzHoCC1P5HwXM9TboAxwtacNy5CsyJj8ys17A\n9UDiBnsW8JSZbQv093ZY0a/1Agaa2Y8ICuQAT98f+EtKsc56VmT2e0Y77ghMSE4kLS9pP0mPEbbc\nmQNsb2YjCxNK6gWsl3FtHeCd1Pm7HnYnQfl9gmDV/x1wu5nNy5BrItn9DvUYg4Qxto6ZbWVmWxP6\nG4rfm1lcBTzj8XtRu8NDVpmQ/wyF7Hu/XM4ysyqgO/Aj+YedQiQd44pwzezZs+tVwP/mL6hXeCQS\nibR0Kvn8KqngmtnZZtYV+H/AhsALkh6tmESRSMvmHTMb68d3kG9ByeNBMzOCAvSBmU0zs0WEF7Mu\nhJf20WY225WjoUCiSH4DJNaECR4fYF3gMUnTCFML0vtUP5B6kR8G7OkvnkcC1YXCmdkk4AeS1law\n7n5qZu8Au/tvEuEltytBsQV4K7VVTlqucjlR0hTgRWC9VL557AT8y8wWmtkHwDOEdgN4ycze9Tad\nnCPLVpLGeHsdTN32us/MFpnZK8AaHrZzqrz3yHDRlNQR6GRmz3jQbZ4OM3sZuJ3Qd0ea2Tc+Bm4H\nDpHUifDR4xGCcvCMmX3iit6wVDG7AddImkz4OLKypJX82ki3zH0EfJiSvanbdievF2b2FMHit7Ir\nS0cTlKhrUl5ANxGUPPzvrd4eHczsBQ+/M5X/7sBh3gbjgNVSdSpHviyG+9/02N0dONPLGQ20A9b3\na0+YWTJ5SMBFkqYCTxIUxqTtl3hWFOn3QtYC0hpQDeHjwTlmto2Z/c37ug4Kbst/Jfy/Lgszm2tm\nP3cFbSKwF3CPgvfAPZK2T0X/kODenEV9xuCbwEaSrpb0E8IHACh+b2axC+HDBD5mE3ftvHGf9wyF\n7Hu/XPZXWJtkksvcLSuSmQ0xsyozq+rcuXNWlFzWadumXuGRSCTS0qnk86ucfXAT3iHsZfcetf/o\nI5HvG5Zz/i21H4zaFUk/3/8uSh0n58sR3AXzWOAvyBCsWsn9ezXwVzN7QMEVdnAqzWLfEDObJ+kJ\ngrVmf6B3TjnDCHPv1yRYdCG8yF9sZv9IR5TUpaAeC4H2lInLuxvBGjVPwbW7WPuVolCWrGdcNbCP\nmU1xd8N+OemXcMFdCrYmWN3S7s23Ag8SrIDDzOxbLen1m6YVwVKfdjvF0yxR72Zq22JsDXxMSkEy\ns7EK7rz9CHNOp7vil4eAE8zssTqBIX1D5UvSpdOI4InwWkE525G6pwhKWGegt5ktkDST2jbOe1Ys\n0e8ZMn1F3b46GjgGuEPBpflWM5uRka4DsBUw2sfFmsADkn4B/I+g7CWs62FpzgYuJMzLfQ64h/AB\nYA+/3s5ly6LsMWhmn/oHtD2AYwnPo+SjW969WRYlxn3eM7RQ/uRGTD/XIeP+cQ+C04A+Xq/qrHhL\nyx82WqvOHFyA9q3EHzZaq0iqSCQSaV76dlox0025FVT0+VXSgusuNU8CYwhfp08ws8yvk5HI94D1\nUxaNXxFeAiF8/EkUxn2XIv+XCC5uq0tqTXjRfKZEmo7UvqiW2qP6JoJb33gz+zQnzl0Ed9GB1FoQ\nHwOOTCyGktaRlDkXNcXnhBfuUrJ/6i+iXQmuuQkLUm6OacYQ3F1bu6vnzoR2K5cOwCzPu9BFN4tn\nU+WtRXBFrYNbjj6V1NeDDsX7TdIvgVVdzqsTBc6twe8Bf6LWRXM8of9XUZgLmR5LjwMnJCdKzafO\noTnadgzepq5ofGRmn0nagGBV3Ab4qSuKCf8kWGlvBTCzOcDnqTgHpuI+BvxWtfN2N0u5DpdDOWMy\nKeeExN1Y0jY58ToCH7py2x/YIHUt81mR0++FzAA2SU7MbJyZHUVov9eAmxXmkPZKJ3Jr7Opm1sXM\nuhAsmL8wsxqC1f9ASW1dKduUVN9K2hRY18xGE+bkLiIo5ekPVpsRFukql8wxqDDVqZWZ3evtkNSj\nvvfmKOC3nmdr96QoNu7ry9tAN2+zTsCuGXFWJnz0mKswp/enS1FeLvuuuSpXbL4e67Ztg4B127bh\nis3XiwtMRSKRFs2wbTalb6e6/6bbSly9xfoVfX6V84V7U+BM/wcZiXzfeQ04TtItwCu4exzBffBm\nSecTXBobhJnNknQmYa6eCG5/mYvNpBgMDJP0KcF9dsO8iGY2QdJn5L9YY2YvK6zC+j8zm+Vhj0va\ngjBFAeAL4BDqzo8spBq4QdJXBFfMLB4FjpU0g9C2L6auDQGmSppodeeKjvD8phBewH9vZu/7y2w5\nnE1wb53tf0spPCMIrpCvAP8FXsiJdzihvisQXDCP8Bf5S4BdzewdhQWj/k7th4ihQOfEGmdm/5N0\nEUHx+AR4FVjsdglc6+6wyxEU72OLyN0cbTuYMJd4KjAPONyVxJuB08zsPUlHAdWS+rg1eihwAfCv\nVD5HATdKWkT4UJC0wU0Et9KJnu9sYB/Kp5rSYxLCIk1/I7RRK+AtwtzMQoYCD7pLbQ2hvxLynhVJ\nusX9nsFIgvXyyXSgmX1BaMub/X4sG7+v73ZZvgWOM7P0/XshYe4xhL64DzgTSBYHa0NQuuvzLpA3\nBtchuKMnH9n/4H/re2+eBAzxMbWQoOwWG/f1wu/ZuwlK/VsEF+TCOFMkTSL0/TvA2MI4jcW+a64a\nFdpIJLLMMWybUrOjGh/VeusUiRS2LEgsE2N8Tlkk8r3C3XEfMrOtmlmUBqOwiNFooKvPVUzqVW1m\n/ZpNsO8prvBOMrObU2ErmdkXbsEdAdxiZlkr7bYIFFb0nWlm1Q1MPxDY28wOTYWt5Moc/sFnLTM7\nqRHEbRJKPSuy+r3genvCR64dC5TQZkPSAKCXmZ3t54NZin7/vlNVVWU1NdFuEIlEIuUiaYKvF1GS\nclyUjyO4Ka7vv7sl1Xfl2Egk0sxIOoxgFTkrUW4jzYekCYRVV+8ouDRYYXGjxGp0X2Ha7wqSriZY\nuM8vuPRzha18phM+rl7Q5MJViCL9vhgLC8OdS7B0thSWA/7S3EJEIpFIJFKKkhZcdzXbIfU1fSXg\neQvbQEQikWUcn1u2T7TERBqCz7WdY7UraUe+B8R+XzqiBTcSiUTqR30suOXMwRVhaf2EBTTu6qKR\nSKQZ8UV9qptbjsiyiS9KFPmeEfs9EolEIi2VchTc24Fxku718wGEPR4jkUgkEolEIpFIJBJpMZRU\ncM3sMoV95HbyoGPNbHxFpYpEIpFIJBKJRCKRSKSeFF1kyveVe9nMXjKzv/ovKreRSKRsJI2WVOXH\nDyf7wLYkJM30LX3qk2awpEFLWW4XX0ipPmlO9q2IkvMvllKGBvWJpEG+km5Dyy2sR7OPDUnVvqpz\nQ9L2lPSzpixf0tqS7ikjXtG2LeyLepQ/yFdmT85vktStvvl42n6SqhuStqlI7rVy272xmfX+/Ywd\n25dRT23C2LF9mfV+qR3kIpFIpPmZMPFQRj218eLfU093q/jzq6iC69sTvCmpJa3kGIlEWii+tU0u\nZvYzn/O7TCOpdQPSLFfsvB6cDNRbGcmjGfukTj2+A2OjJ7BUCm59MbP3zKykQlxG2+aOqRJjfRCw\nWME1s1+b2Sul5FnWKbfdG5NZ79/Pq6+exdfz3wOMr+e/x6uvnhWV3Egk0qKZMPFQ5sx5vk6Y2Xxe\neeW0ij6/Sm4TBKwEzJD0mKThya9iEkUikWZH0mGSpkqaIul2D9tL0jhJkyQ9KWkNDx8s6XZJY4Hb\nJbWX9G9JMySNANqn8l1sKZV0qqTp/jvZwy7xrclI5X2apJUkjZI0UdI0SXv79RUljXQ5p0s6wMP7\nSHrew1+S1MGtTdek8n7IV4ItrPt9kiZIelnSManwLyT9RdIUYPuCNNtKesHb5nlJm3v4IEkPSHoK\nGOVWqjGSHgASRaC1pBu9vMe9/TaWNDGV/6Ze9xMJCsXTkp5OXb/Q6/piql+qJV3vYW962bd4v1Tn\n9MkSdVfw5Kn29p0m6ZSMNuvi9Zrovx08vJ+CBf8eSa9KGqrAEvUokCNr/HWR9JSHj5K0folx2VnS\nE16XmyS9LWl1FVjNfXwNzqjTOZLGe72HSJKHj5Z0qY+r1yX1lbQ88GfgAIXtjQ4os30k6RpJr0l6\nEvhBQb9c7PnVSOql8H/4P5KOTeU7PTXWhkt6VNIbki4r7GNl3C85fVFnrGe1hYKluQoY6jK2V11v\njYN8vEyXdGlKli+UMV4z2v8MTz9F0iUe1tPTTJU0QtIqqT5Jyl1d0sxUm9zn42CmpOMVnjuTPJ9V\nPd7RXr8pku6VW7MlbahwX0+TdEFKtrLavTF58z9XsGjRV3XCFi36ijf/c0UliotEIpFGoVC5rWVR\nRZ9f5Si4FxAWlroMuDb1i0Qi30EkbQn8CdjFzHoAJ/ml54Afmtk2wL+B36eSdQN2M7ODgN8C88xs\nC8Jenr0zyugNHAFsB/wQOFrSNsBdwP6pqPt72NfAADPrBfQH/uIKx0+A98ysh5ltBTzqysZdwEku\n/25A3TfD4hxpZr0JL+8nSlrNw1cExnlZzxWkeRXo621zDnBR6lovYKCZ/Sh1fpKZbebnmwLXmtmW\nwBxgXzP7DzBXUk+PcwRwq5ldBbwH9Dez/im5XvS6PgscnSp7FYIyfgrwAHAlsCWwdSrvUnXvCaxj\nZluZ2dbArRnpPgR+7P1zAHBV6to2BAthN2AjYMecegBFx9/VwG2+Rd3QVBl54/Jc4Clv13sI+7jX\nh2vMrI+Pq/bAnqlry5nZtl6vc83sG0K/32VmPc3srjLbZwCwubfNYcAOBen+a2Y9gTGElc4HEu6X\n83Jk7un5b01QttcruL7E/VJkTKXH+hJtYWb3ADXAwV7nxfeYgtvypcAuLlMfSfuk8s4br0n6nwJ7\nA9t5vERp/Cdwho+BaYQ+LsVWwC+BPsCFhGfTNsALhDYHGO716wHMAI7y8L8D1/u4n1WkjFLtntTr\nGP9YUTN79uwyRK/l6/nZxeeFRyKRSEunks+vkgqumY0CpgJtgeWBqR4WiUS+m+wCDDOzjwDM7BMP\nXxd4TNI04HSCopTwQOoFd2fgDk87lfD8KGQnYISZfel7bA8nKIiTgB8ozHHrAXxqZu8Qtia7SGFf\n7ieBdYA1CC+5P1awqPU1s7kEhWFWsl6AmX1mZt/Wo/4nuuXqRWA9ggIKsBC4NydNR2CYW3USJTLh\niVQbArxkZm+lzt9K7SU6AejixzcBRyi4iB4A3JlT9jfAQxnpAR60sNn5NOADM5tmZouAlwviJWTV\n/U1gI0lXS/oJ8FlGujbAjT42hhEUtnR93/VyJ+eUmyZv/G1PbRvcTu3Ch3njcieCwouZPQp8WqLc\nQvorWIanuUzpPk28mArbO4+89tkZ+JeZLTSz94CnCtI94H+nERTOz81sNjBf2XNqR5nZXDP7muAh\nsEHB9az7JYvCsV6sLbLoA4w2s9l+7w31ukLx8ZqwG+GDzjwIY0BSR6CTmT3jcW5L5VmMp1PtNhd4\n0MOnpcreSsHCPg04OFW/HYF/+fHtRcoo1e54PYaYWZWZVXXu3LkM0Wtp13ateoVHIpFIS6eSz6+S\nCq6kI4CJwK+AQ4AaSYdXTKJIJNJSuZpgydka+A3QLnXty0YsZxjBUnUAwRIL4aWzM9DbLVofAO3M\n7HWCRXQacIGkc4rk+y11n3ntCiMouCzvBmzv1pxJqXhf+7oEWZxPeJHeCtiL4m1TeD4/dbyQ2tXt\n7wV+SrAcTjCzj3PKXuBKbGH6dN6LCspZVBAvt+5m9inQAxgNHEtQvAs5hdAnPQjW3+XLqF9jUWxc\nZlHOOGgHXEewvG8N3FgQL6lTufUp1j7FKLv/CuJnylaP+2XxWC+jLepLsfHaUNJ9WihbYbul2zQp\nuxo43ut3XkEeRmkqPcbZaOPTaNWqfZ2wVq3as9HGpzV2UZFIJNJodOpU6JiU0Kqiz69yXJTPBHqZ\n2SFmdjDhn/MfKyZRJBJpbp4C9ktcc5N5agQr5f/8uNhHrmcJH8SQtBXQPSPOGGAfSStIWpHgqjnG\nr90FHEhQcoelyv7QzBZI6o9bSNwVcp6Z3QFcTnh5fw1YS1Ifj9NBYUGnmUBPSa3chXDbDLk6EqzG\n8yR1JbiDlkO6bQaVmaYobg16DLieum7BnwMdGqOMAjLrrjAvtpWZ3UtwHe6Vk3aWW2kPBcpZhCuv\nHnnj73nCuIDwwSMZL3njcizu7i5pd4K7NgRF8weSVpPUlrquxwmJgvORpJUIY7Gh9UlkzGqfZwku\nra0lrUVwv68YOfcLFJe9WFvkpXsJ+JHPh20NHAQ8kxEvjycI3gvJXNhV3dr8qaS+HufQVJ4zqZ0K\n0ZDFnzoAsyS1IYythLHUHXPNxlpr7k3XrhfSru3agGjXdm26dr2QtdbcuznFikQikaL07nX7Ekqu\n1JZu3a6o6POrnK+MnxDmhSXM8bBIJPIdxMxelnQh8IykhQRL3iBgMMEN91OCErJhThbXA7dKmkGY\nzzYho4yJCgsdveRBN7l7clJ+B+B/ZpZM0BgKPOguhDWEOa8Q5rxdLmkRsAD4rZl9o7DIz9WS2hPm\n3+5GeFl9i+BCOIPgmVLIo8CxLvtrBFfdcrgMuE3Sn4CRZaYph6EE5f/xVNgQwlzj9wrnry4leXVf\nh9CfyQfRP2SkvQ64V9Jhnk85Fv3MehQZfye4HKcDswnzkiF/XJ4H/EvSoYT5lu8Dn/tHkj8Txt7/\nqB1LizGzOZJuBKZ7unK2x3saOFPSZODignm4ee0zguDy+wrwX5ezkixxv3h47pgq0RbVwA2SviK1\n8JqZzZJ0JqFNBIw0s7KXyzSzR32OeI2kb4CHCR/WD/fyViC4zidj4ArgboWF0Rpy/50NjCOMq3HU\nKu0nAXdKOgNo9uWK11pz76jQRiKRZY7evYrN8KgMqvUUyokQXkK3Au4juOrsQ/hHl7yMXpWbOBKJ\nRL6jKKy8O9PMqitYxmlARzM7u1JlNBSFPYC7mNngZhYlE7fOLjSzbyVtT1gsKGthrUgLwF3kB5nZ\noGYWpUmoqqqympqa5hYjEolElhkkTTCzqnLilmPBfcd/bf38Uf9bvxUSIpFIJFI2ClssbUyw8EXq\nz/oEq14rwsJGS6zWG4lEIpFI5LtHSQW3JVoOIpFIpAUwmrrTNxoVMxtQqbwbicmEuY8tEjN7g7BF\nUWTZYCbBUywSiUQikaWi0Vf6i0Qike8DZja6uWVoTlJbG0UiS42ZzaQFfzCJRCKRyLJDOasoRyKR\nSCQSiUQikUgk0uKJCm4kEolEIpFIJBKJRL4TlHRRlnQxcDEwj7D8fk/gFDO7s8KyRSKRSL3x1X2r\nzOz45pYlD0ldgGoz67cUefQDTjOzPSX9AuhmZpcUiT8Y+MLMrmhAWVXAYWZ2YkPlbSrS7dKEZbYB\nxplZr4LwL8xspSaUYzSh7i12ed5yxr7v3vCQmd2zlGWdDAwxs3lLk09LYerUqYwaNYq5c+fSsWNH\ndt11V7p3z9pmPBKJRFoOt912G2+99dbi89atW7P33ntX9PlVjgX3p2b2GbAn8B7QFTijYhJFIpHI\ndwBJ9V7jQIF6e9aY2QPFlNulxcxqGlu5bUj7VIKGtnkBOxH2WW5I+S2iHb6jnAys0BgZNXc/TZ06\nlQcffJC5c+cCMHfuXB588EGmTp3anGJFIpFIUQqVW4CFCxcyYsSIij6/yvmnnjzUfwYMM7NPCfvh\nRiKRSEWR1EXSq5KGSpoh6R5JK/i1mZJW9+Mqt14Vpq+WdL2kFyW9KamfpFs8r+pUvIMkTZM0XdKl\nqfAvJF0oaYrnsYaH7yVpnKRJkp5MhQ+WdLukscDtkp6V1DOV33OSemTU8TVJ/yTsMb6ey1wj6WVJ\n56Xi/sTbYyLwy1T4IEnXpPJ7StJUSaMkrZ/RLj29PlMljZC0iof38bDJki6XNN3D+0l6yI9XknSr\nt9dUSftm5D9T0mUe5yVJm6T64wZJ44DLJK0q6T7P50VJ3YuVIWl3SS9ImihpmKSVSrTLYIW9hJPz\n6d4+WW2el/clkl5xOfKs3z8BHsm6IOlK78dRkjp72GhJf5NUA5yU12feXldJet7H78BUvmd4+0yR\nlP64sZ+3+euS+nrcdqn2nCSpv4dv6XEne9mbevhhfj5F0u3FxlWqT2u8zD09vOTYzyvL2Tmn3qdL\nGu9pzvOwFSWN9DymSzpA0onA2sDTkp4uKLOj9//mfv4vSUtsI6VwXz0g6SlglI/LUT5Gpkna2+P9\nWcFanKS7UNJJWeOhoYwaNYoFCxbUCVuwYAGjRo1qzGIikUikUSlUbhPMrKLPr3IU3EcUXnK2A55Q\neKGcXzGJIpFIpC6bA9eZ2RbAZ8Dv6pl+FWB74BTgAeBKYEtgawVFb23gUsJ+sz2BPpL28bQrAi+a\nWQ/gWWr3Un0O+KGZbQP8G/h9qrxuwG5mdhBwMzAIQNJmQDszm5Ih46Zexy3N7G3gLN/MvDvwI0nd\nJbUDbgT2AnoDa+bU92rgNjPrDgwFrsqI80/gDI8zDTjXw28FfmNmPYGFOfmfDcw1s609/VM58eaa\n2dbANcDfUuHrAjuY2anAecAkz+ePLldmGf6/50+Etu0F1ACn1qNdClnc5sCXOXmvBgwAtnQ5LsjJ\nqz9h26hCVgRqvIxnqG1ngOXNrMrM/kLxPluLYCHeE7gEQNJPgb2B7XxsXpaKv5yZbUuwXiblHQeY\n98dBwG3ebscCf/f+rgLelbSlt8UunneiqBWTsQuwLfBz4AbPu+TYL1JWXr13J/TbtoR7tbeknQkf\nGN4zsx5mthXwqJldRfA6629m/dPlmtlc4HigWtKBwCpmdiPZ9AIGmtmPgK+BAT5G+gN/kSTgFuAw\nl7EVcCBwR2FGvJcDPAAAIABJREFUko7xDwE1s2fPzikum8RyW254JBKJtHQq+fwqR8H9A+HFr7eZ\nLSA84Jf4Yh+JRCIV4h0zS9w/7yC89NaHB83MCIrcB2Y2zcwWAS8TXsz7AKPNbLaZfUt4ed/Z034D\nPOTHEzw+BCXtMUnTgNMJCnPCA2b2lR8PA/ZUmKN5JFCdI+PbZvZi6nx/BWvkJM+7G2F6yFtm9obX\nZ4kXaGd7IFkj4XYK2ktSR6CTmT3jQbcRrGWdgA5m9oKH562zsBtwbXLiXj1Z/Cv1d/tU+DAzS5Tn\nnVxGzOwpYDVJK+eU8UNCO4yVNBk4HNiA8tulkHSb5+U9l/A/72ZJvySsRVEHSesAn+TM81wE3OXH\nhWP3rtRxsT67z8wWmdkrwBoethtwa1KmmX2Sij/c/6bH605ePmb2KvA2sBnwAvBHSWcAG/i43YXQ\nRx8V5F1MxrtdxjeANwl9Us7Yzysrr967+28SMNHL2ZRwb/9Y0qWS+roCWxQze8LTXQv8ukjUJ1Jy\nCbhI0lTgSWAdYA3f4uhjSdsk8pnZxxllDvGPGlWdO3cuJWIdOnbsWK/wSCQSaelU8vlVjoL7kpl9\n6C9+mNkXBCtIJBKJNAWFUyKS82+pfYa1K5I+8ThZRF3vk0WUXmhvgStNECyaSfyrgWvcIvabgvK/\nXCxoUECeIFjb9icoz1ksTiNpQ+A0YFe3lo2keP1aKpZz/GVhxDIRQdno6b9uZnZUiTTpMQI5/ZSX\nt//f2xa4h2BJfDSjjJ8Aj5VZh4a0Q3rMqh7x0+M1W5iwWOQvgK+AhyXtUqZMS2S1ZNZlj/08suot\n4OJUP21iZjeb2esES+s04AJJ55TK3C2tWxA+WiQu+gPcXXuywsJqULefDgY6Ez749wQ+oHZM3USw\nWB9BsOg2Krvuuitt2rSpE9amTRt23XXXxi4qEolEGo0NN9wwM1xSRZ9fuQqupB/4fJn2krZ2F7nu\nknaikRZtiEQikTJYX1JiAfwVwT0YYCbBJRWWzqvkJYIb8OqSWhNcOJ8pkaYj8D8/PrxE3JsI7pzj\ni1g706xMeKmeqzC396ce/irQRdLGfn5QTvrnCS6SEF7Ix6QvunXr02R+JnAo8IyZzQE+l7Sdhx9I\nNk8QXF4BkM/fzeCA1N8XcuKMcRmT1Y8/srCoYVYZLwI7qnY+74ru+lqsXWYSFB8k9QKy/9Pm5K0w\nD7ejmT1McHFfYg4pRebfEv7HJvNH02O3kKJ9lsETwBGqnY++aon46XbeDFgfeE3SRsCb7s57P8El\n/inCPN7VCvIuJuN+klp5H2wEvObhpcZ+Xll5PAYcqdr50ev4u8rawDwzuwO4HO9z4HOgQ05epwAz\nCP1yq6Q2ZjYipTxnrUTdEfjQzBYozGPeIHVtBGEs9KH8Dx5l0717d/baa6/FFo+OHTuy1157xVWU\nI5FIi+bwww9fQslt3bo1AwYMqOjzq9jX3Z8T3IrWBa5LhX9OmB8ViUQiTcFrwHGSbgFeAa738PMI\nrqPnkz3/sSzMbJakM4GnCRaikWZ2f4lkg4Fhkj4lvKTnKU6Y2QRJnxHmt5YjzxRJkwiK2zv46rxm\n9rWkY4CRkuYRFIysl/cTCC/spwOzCRalQg4nzJVcgeBSmsQ5CrhR0iKCkp/l6nkBcK2vzbCQ0A/D\nM+Kt4q6c88lXxgcDt3i8edR+LFiiDDMbrrAF1L8ktfV4fzKz14u0y73AYZJeBsYBr2cJYWazs/Im\n/L+73+eUCjg1nc4/iGzibr9ZfAlsK+lPwIfUKv2FlNNnaXkfVVjAqUbSN8DDhDnMeVwHXO8u9d8C\ng8xsvqT9gUMlLQDeBy4ys08kXQg8I2khwR14UAkZ/0v4ULQycKyZfe1yFh37ZvZyTll59X5c0hbA\nC2HqK18AhwCbAJf7uF0A/NaTDAEelfReeh6uwuJSvwa2NbPPJT1L6O/0HOkshgIPejvWEO7RRLZv\nFBazmpNywW9UunfvHhXaSCSyzHH44aXsAI2Par3vciJI+5vZ3U0kTyQSiSxGYc/Mh3zhmGUSty6N\nBrr63N9G2Qe3Ekhayaeh4Er/WmZW79VgJc0k7EX8USOL2KJwj6ZDzOzY5paluVCRPWuXpbG/tLjL\n80RgP5+LXJSqqiqrqWmx2xVHIpFIi0PSBAsLcJaknH3d7vOvvF3S8c3sooaJF4lEIt8PJB0GXAic\nmrzgt3B+LukPhGf92xSxpkXAzJ4j3+34e80yOPYbjKRuhMXoRpSj3EYikUikspRjwR1JWEVyAqlt\nI8zs0txEkUgkEslFYcXifcysurlliUSakjj2A9GCG4lEIvWjsS24GyzL7oGRSCTS0vAFnaqbW45I\npKmJYz8SiUQilaacbYJedPebSCQSiUQikUgkEolEWizlWHC3AyZJ+j/Capgi7HHXq3iySCQSiUQi\nkUgkEolEmo5yLLj7AN0Im8HvR9jTb79KChWJVAJJz5cRp6+klyVNltS+nvnvk/Z2kPRnSbs1RNb6\nImmwpNOautxykTRI0uAK5Z2s+ru2pCVWci0zj0G+4mtyflNje674ysLJ8R9Tx118O5wWTVOP72J9\nkvT5UubfSdLvGpj2YZ9LWizOTEmrF7k+2LcmanbKuYckjZZUdO5TQ+uULldST0k/K8jztPrmWWnK\nGQONzZeTPmTWJS/x7pljmHXJS3w56cOmLD4SiUQaxAc3TuHdM8fU/v70XMWfXyUVXDP7D9AZ2NGP\n5xD2mYtElinMbIcyoh0MXGxmPc3sq3oWkXwMSso7x8yerGceS01zldvcmNl7ZjawgckHAYuVKTP7\ntZm90iiCZVNsz9J6IakcT5zGoKnH9yAq2yedgHopuAq0MrOf+VzSZYJyx8hS3kMNpqDcnsDPisUv\nJOmXxpcsn6YeA19O+pA5w99g4Zz5ACycM585w9+ISm4kEmnRfHDjFBb857O6gd8an979WkWfXyX/\nIfgG9ecSNkEHaAfcWTGJIpEKkbJS9HNrxD2SXpU01F+Qfg3sD5wvaajHPV3SeElTJZ2XyuswD5si\n6XZJOxC8HC536+/GkqolDfT4u0qaJGmapFsktfXwxVYeSVWSRvvxjzyfyZ6uQ0Z9zpL0uqTngM1T\n4elyL5H0ist6hYd1lnSv12u8pB09fFtJL3h5z0va3MO3lPSSyzJV0qYefkgq/B+SWvuvWtJ0r+sp\nGXIPknSfpCe8/sdLOtXLfVHSqh5vY0mPSpogaYykrh6+ocs5TdIFqXwXW0JdjitcjqmSTvDwc7zO\n0yUN8X4fCFQBQ70u7ZWyVkk6yMuaLunSVHlfSLrQx8CLktbw8P087hRJz2bU/xKgvZc11INbS7pR\nwXvgcbn3QJE2qJZ0g6RxwGVF+m6QpPu9Pm9IOjclxxL9l9QrFWegl1VqfPfxcqd4nnXGq6SVJI2S\nNNHbcu9Un80orHupPvG0V3qaUZI6e9jR3r9TFMb4Ch6+hqQRHj7F63MJsLHnf7nHW+J+dxlfk/RP\nYDqwnuret/d5/7ws6ZiM/l5R0kgvd7qkAzLiDJZ0m/fx25J+Kekyb6tHJbXJG78evomkJ72Mid4/\n/Ty/B4BXPN6pnna6pJMz5EjfQ+0l/dv7ZwTQPhVvdx9vEyUNk7RSRl55Y/Im1T7bZks6NylX0vLA\nn4ED/HrSVt28/9+UdGKRfil2r17uffSky5bk9wuP86yknqk0z0nq4WP3Vs93qqR9/fpMSasrZwwX\ntsfS8tljM7EFdXdbsgWL+OyxmY1dVCQSiTQaSyi3CUZln19mVvQHTCbMu52UCptaKl38xV9L+wFf\n+N9+wFxgXcJHnheAnfxaNTDQj3cHhvj4b0XY53BnYEvgdWB1j7dqYdr0OeGj0DvAZh7+T+BkP56Z\nyqcKGO3HDxK8JgBWApYrqEtvYBqwArAy8H/AaQXlrga8Ru12YJ38752p+q4PzPDjlZNygN2Ae/34\nauBgP16e8KK7hcvYxsOvAw5zuZ5IyZmUOQgYnDr+P6ADwTtkLnCsX7sy1TajgE39eDvgKT9+ADjM\nj49L9WsXYLof/xa4J1WfVdN//fh2YC8/Hg1Upa6N9v5YG/ivy7kc8BRhixMAS6W/DPiTH08D1knX\nP+nrwrGYkvtboKef3w0cUqINqgnjsXWJvhsEzCKMhfYERaAqr/8yZBsIVJcY38sDbwJ9CmVJxV0O\nWNmPV/f+V4m6Z/ZJqu2TMXkOcI0fr5aKfwFwgh/fRe24ag10JDVeStzvXYBFwA/TfcmS93/Svqul\n4wD7Ajem0nb0v4OBQanj54A2QA9gHvBTvzaC2jGXN37HAQP8uB3hudAP+BLYsOCZsSLhmfIysE3B\ns3FxmwCnArf4cXfvpyqv07PAin7tDOCcjDpljsmU/BsAM/xvutxBSX+m8nweaOtlf+ztVKdfKH2v\nptvz8VRbT/bww4G/+fFmQI0fX5qE+/kqBf3bhZwxXPgDjgFqgJr111/f6sM7Zzyb+4tEIpGWSrFn\nV32fX8lzuZxfOW5L883MJBlA8kU8ElnGecnM3gWQNJnwkvJcQZzd/TfJz1cCNiW8FA0zs48AzOyT\nEmVtDrxlZq/7+W0ExexvRdKMBf6qYOEbnsiaoi8wwszmeR0eyMhjLmEP65slPUR4YYfwstnNjT8A\nK7sFpiNwm4KF1ggvgBA+AJwlaV2X5Q1JuxJemMd7Pu2BDwlK00aSrgZGEl4ks3jazD4HPpc019NB\neAHv7vLsAAxLydnW/+5IUBogvORn7cm9G3CDmX0Ldfqov6TfExSAVQkv+Q9mpE/oQ/joMBvA+2Nn\n4D7gG2rbdALwYz8eC1RLuhsYXiTvNG+Z2eRUXl1KtAGEMZjsTZ7XdxA+OHzs8g8HdiK8kGf1X0PY\nHJhlZuMBzCzrc62AiyTtTFBK1gHW8GtL1L2MMhcRlFaAO6ht560UrPqdCPfrYx6+C+EDDN5mcyWt\nUpBn3v3+X+BtM3sxR5YTJQ3w4/U8zcep69OAv7hF8SEzG5OTzyNmtkDSNIIS/mgqfRc/XmL8Knh9\nrGNmI7x+XwN4v75kZm952p0Iz4wv/fpwwnMkqW8hOwNXeZ5TJU318B8SXNXHehnLE54RheSOSUnt\ngGGEDxBvS+qSkT7NSDObD8yX9CG1YyfdL6Xu1XR7zk+1dVL2MOBsSacDR1K7ldFuwIGJIGb2aYZ8\nZY1hMxtC+IhCVVWVlahzHVp3arvYPbkwPBKJRJZFKvn8KkfBHS7pWqCjpCOAo4BbKiZRJNI0pN8U\nFpJ9L4gwH/cfdQLd3bWR+JbaqQLtkkAzu0TSSMJctLGS9jCzV+uTsZl9K2lbYFeCpe14wot+K4LV\n4+t0fEnXEBTPAf7COdrzuVPBFfbnwMOSfkNom9vM7A+F5UrqAewBHEtw+T4yQ7x0+y9KnS8i9EUr\nYI6Z9SxMmFSvaOUz8Jfq6whWwHcUFr1qVzxVURb4F0VIjSEzO1bSdoT2miCpd6JgFqFwPLandBt8\nmTo+n4y+cwrbyijSfwXxl6Z90hxMsKz1dsViZirvrLrXl0TmaoLVborCYkf96pFH3v3ehbptnb7W\nj6AAbW9m81zZrNNmZva6pF6Ee/kCSaPM7M8Z2c33+IskpcfWImC5Bo7fTLmXEhE+mhxUIl6xMXkD\n4WNZuXO4857X5davsD3TbZ3ct/MkPQHsTXhu9S4z7yz5Gt1FeeU9ujBn+Bt13JTVphUr79GlsYuK\nRCKRRqPNxitnuymLij6/yllk6lKCleIBguXqQjMrZnmKRL4rPAYc6ZY0JK0j6QcE17f9JK3m4at6\n/M8JbreFvEawyG3i54cCz/jxTGpfpBKrJJI2NrNpfv+NB7oW5PkssI/CPLkOwF6FhSZWWTN7GDiF\ncP9CsKqekIqXKFAdgf/58aDU9Y2AN83sKuB+grviKGCgtweSVpW0gcK8xFZmdi9h3n6DthNzK+Bb\nkvbz/OWKMwQLaWJROTgniyeA3yQvr95HiTLwkbdNejGdvL57CfiRz7VrDRxEbd9l4n03zszOAWYT\nrHqFLJDPq8yjRBsUktl3zo+9f9oTFooaS07/efwPJG2hsGjPgFQ+xcb3WpL6eF4dtOSiRh2BD125\n7U9wSy1FXnkQ/ncl/fcrar0vOgCzvG3TY2MUwW09mZ/dMSP/vPu9GB2BT1056kqwbtZBYSXoeWZ2\nB3A5DbwnyBm/7gnxrqR9vLy2yva0GkN4ZqwgaUVC3+ZZkyE8Y37leW5FuO8BXgR2TJ5nCnOMN8tI\nn/c8OQ7oYGaX5JRbrN+LUe97NYObCFbr8SlL7RMEjxsAMiz/TcKK2/yATr/cdLHFo3WntnT65aas\nuE2pIRqJRCLNxxpH96DNxivXDVxOrLL/5hV9fpW7suIjkp5J4ktaOccNLRL5zmBmj0vaAnjBXfG+\nIMytelnShcAzkhYSXPwGAf8GblRYBGVgKp+v3fthmL/4jydYMADOI7gQn09dC8fJrggsIrjRPlIg\n20RJdwFTCK6l4zOq0AG43y0/IsypAzgRuNZdDpcjvMgeS5hHepvCwnIjU/nsDxwqaQHwPnCRmX3i\n8R53RWgB4SXwK+BW1a5ommUhLJeDgeu9nDaE9p0CnATcKekMgsKdxU2EeXRTXe4bzewaSTcS5km+\nT902qwZukPQVsH0SaGazJJ0JPE1ow5FmlldmwuUKbpkiKFZTMuIMcdkmAmcVySuvDQrJ6zsIL/73\nEuac32FmNbB4AcHC/nsbOJPwUXM2Yb5gsoBQ3vj+RmExoKtdif6KYNVMb+UzFHhQwSW0BijHG6Ga\njD5xvgS29Tp8CCSLEZ1NmI862/8mitJJwBBJRxEsbL81sxckjVVYVOkRMzs96373+Hk8ChwraQZB\n0c9yY96aMCYWEdr5t2XUfQnMbE6R8Xso8A9Jf/YyltjKz58Z1YTxAHCTmeW5JwNcT7iXZxDmyk7w\nfGYrWMf/JV8sj/Ax6/WC9Hlj8jTCB57EpfcGat2HIdxrZ/r1i4vIV1i/htyrhXlMkPQZcGsq+ALC\n83I6YSycR/lTDxqVFbf5QVRoI5HIMscaR+d9m68cyeIz+RHCyrLnEx7siwj/OMzM1q+8eJFI5LuA\nvxB3MbPBzSxKsyFpppl1aeIyBxFcWo9vynIjpVFwMZ5pZtXNLEqjsazXya3to4GuZraoRPSloqqq\nympqaipZRCQSiXynkDTBzIrux55QjgX3DKCHmcXN1iKRSCQSiXznkHQYcCFwaqWV20gkEolUlnIU\n3DeB6I4ciUSWhsmE+cbfZ5p87QK3pFU3dbmRshgNzGluIRqZ0SyjdTKzfxK2cItEIpHIMk45Cu6Z\nhFVcXyS1UqCZnZqfJBKJRGpJbaHxvSUuzhdJY2ajm1uGxua7WKdIJBKJLHuUo+DeQFh1cxphDm4k\nEolEIpFIJBKJRCItjnIU3LZmdmLFJYlEIpFIJBKJRCKRSGQpKLkPLjBS0pGSOktaOflVXLJIJNIg\nJD1fRpy+kl6WNNm3dqlP/vtI6pY6/7Ok3Roia32RNFjSaU1dbrlIGuQryVYi7y/879qS7mlgHoN8\npdjk/KZ0XzYGkmamjv+YOu7iW620aJp6fBfrk6TPlzL/TpJ+18C0D0vqVCLOTIX9r/OuD/bVvL9T\nSDrWF6ZqMmaMeZohxx3BXw7ciyHHHcGMMU83ZfGRSCTSIO4+/yz+csCei39/O2RAxZ9f5Vhwkwf4\neakwA+I2QZFIC8TMdigj2sHAxWZ2RwOK2IewT+orXt45DchjqWmucpsbM3uP1D609WQQYR/V9zyv\nXzeSWHn8EbioMTKStJyZfdsYeZWgqcf3ICrbJ52A3wHXlZtAYSNgmdnPGlmW7wxmdkPpWI3HjDFP\n8/iQa/j2m7AUyucfzebxIdcAsEXf/k0pSiQSiZTN3eefxTvTp9QJW7hgAY9c+1egcs+vciy4G5nZ\neukfsHFFpIlEIktNytLXT9JoSfdIelXSUAV+DewPnC9pqMc9XdJ4SVMlnZfK6zAPmyLpdkk7AL8A\nLnfr78aSqiUN9Pi7SpokaZqkWyS19fDFVh5JVZJG+/GPPJ/Jnq5DRn3OkvS6pOeAzVPh6XIvkfSK\ny3qFh3WWdK/Xa7ykHT18W0kveHnPS9rcw7eU9JLLMlXSph5+SCr8H5Ja+69a0nSv6ykZcg+SdJ+k\nJ7z+x0s61ct9UdKqHm9jSY9KmiBpjKSuHr6hyzlN0gWpfBdbQl2OK1yOqZJO8PBzvM7TJQ3xfh8I\nVAFDvS7tfXxUeZqDvKzpki5NjydJF/oYeFHSGh6+n8edIunZjPpfArT3soZ6cGtJNyp4Dzwu9x4o\n0gbVkm6QNA64rEjfDZJ0v9fnDUnnpuRYov+SeqXiDPSySo3vPl7uFM+zzniVtJKkUZImelvuneqz\nGYV1L9UnnvZKTzNKUmcPO9r7d4rCGF/Bw9eQNMLDp3h9LgE29vwv93hL3O8u42uS/klQuNdT3fv2\nPu+flyUdk9HfK0oa6eVOl3RAwfVWnl+nVNgbLvNeksZ5vz6ZGmODFZ4joyW9KenEVNo6z6ZUHZ7y\n8FGS1k+No+t9/L6p8Gy8xfuk2uMcKelvqfyPlnRlkbLS3iSjJV3qY+J1SX0L22dpGfPvfy5WbhO+\n/WY+Y/4dF36ORCItl0LlNsHMKvr8KkfBHVdmWCQSaXlsA5wMdAM2AnY0s5uAB4DTzexgSbsDmwLb\nAj2B3pJ2lrQl8CdgFzPrAZxkZs+n0vY0s/8kBUlqR9iS5gAz25rgIfLbEvKdBhxnZj2BvsBX6YuS\negMHulw/A/oUZiBpNWAAsKWZdQcSZfDvwJVm1gfYF7jJw18F+prZNsA51FoYjwX+7rJUAe9K2gI4\nwNutJ7CQYP3uCaxjZlt5XW/Nqd9WwC9d7guBeV7uC9R6xwwBTjCz3t4eiaXt78D1nv+snPyPAboA\nPb3uiSJ5jZn1MbOtgPbAnmZ2D1ADHOx9t7itFVxkLwV28br1kbSPX14ReNHHwLPA0R5+DrCHh/+i\nUDAzOxP4yss62IM3Ba41sy0J28nsW6INANYFdvCV+/P6DsL43RfoDuyn8CElr/8yKTG+lwfuItwH\nPYDdKBivwNfAADPrBfQH/iJJeXUv1ifOikCNp3kGSBT34d6/PYAZwFEefhXwjIf3Al4m7ITwH8//\n9Lz7PSXjdWa2pZm9XSDLkd4/VcCJft+l+Qnwnpn18HH3aEHbLgLuJ9yrSNoOeNvMPgCeA37o/fpv\n4PeppF2BPVzecyW1yXo2edyrgdtS98JVqXxWAbYHTiH08ZXAlsDWknoCdwN7SWrj8Y8AbilSViHL\nmdm2hOftuVkRJB0jqUZSzezZs3Oyyebzjz+qV3gkEom0dCr5/Mp1UZb0A2Atwhf4rYHkn/TKwAoV\nkygSiTQmL5nZuwCSJhOUoecK4uzuv0l+vhLhRbcHMMzMPgIws09KlLU58JaZve7ntwHHUXz/17HA\nXxUsfMMTWVP0BUaY2TyvwwMZecwlKBY3S3qI4F4KQQHpVqtfsLKklYCOwG0KFloDkhfaF4CzJK3r\nsrwhaVegNzDe82kPfAg8CGwk6WpgJPB4Tv2eNrPPgc8lzfV0EFal7+7y7AAMS8nZ1v/uSK0CeDtB\nAS1kN+CGxHU31Uf9Jf2e8KxelaDoPJiRPqEPMNrMZgN4f+wM3Ad8Q22bTgB+7MdjgWpJdwPDi+Sd\n5q3UllETgC4l2gDCGFzox3l9B/CEmX3s8g8HdgK+Jbv/GsLmwCwzGw9gZln7wwu4yBXGRcA6wBp+\nbYm6l1HmIoJSDXAHte28lYJVvxPhfn3Mw3fBP5x4m82VtEpBnnn3+38JCueLObKcKGmAH6/naT5O\nXZ9GUOgvBR4yszEZedxF+DBxK+HDVVK3dYG7JK0FLA+8lUoz0szmA/MlfUhoz13IfjZtT/igBOGe\nuSyVz4NmZpKmAR+Y2TQASS8DXcxssqSngD0lzQDamNk0Ba+Icp6DSd/k9q2ZDSF8zKGqqspy8smk\nw2qr8/lHSyrFHVbLnf4ciUQiLZpKPr+KzcH9OXAk4R9P+mv658DZFZMoEok0JmmftoVk3/MizMf9\nR51Ad3dtJL6l1mOkXRJoZpdIGkmwzo6VtIeZvVqfjM3sW0nbArsS5qYeT3gBbkWwCn2dji/pGoLi\nOUBSF2C053Ongivsz4GHJf2G0Da3mdkfCsuV1INgWTqW4PJ9ZIZ46fZflDpfROiLVsActy5mVq9o\n5TNwS/p1QJWZvaOw6FW74qmKssDMEjkWjyEzO9atcD8HJkjqnSiYRSgcj+0p3QZfpo7PJ6PvnMK2\nMor0X0H8pWmfNAcDnYHeZrZAYcGtJO+suteXROZqYB8zm6KwgFO/euSRd793oW5bp6/1I3xM2d7M\n5ilMMajTZmb2uqRehHv5AkmjzOzPBVm9AGyi4Gq9D7XeFlcDfzWzB7yswak05TzDyiF97xXel0me\nNxHmjb9KvldGqfyXRsZc+h54WJ05uADLLd+Wvgc26TpXkUgkUi/W26pHppuypIo+v3JdlM3sVjPr\nCxxlZn1Tv5+Z2bCKSRSJRJqax4Aj3ZKGpHXcg+Mpgqvnah6+qsf/HFhirizwGsEit4mfH0pwqwSY\nSbCkQa1VEkkbm9k0M7sUGE9wR0zzLLCPwtzEDsBehYUmVlkze5jgftjDLz0OnJCKlyhQHYH/+fGg\n1PWNgDfN7CqCK2V3YBQw0NsDSatK2kBhXmIrM7uX4L7YK6M9SuJWwLck7ef5yxVnCBbSA/04z632\nCeA3kpZL5KNW8fjI2ya9IFVe370E/EjS6gpzVA+itu8y8b4bZ2ERptkEq14hC1Iun5mUaINCMvvO\n+bH3T3uC8jSWnP7z+B9I2kJSK9xt1ik2vteS1Mfz6pC0e4F8H7py2x/YoDCTDPLKg/A/Oum/X1Hr\nfdEBmOVtmx4bo/BpAQrzsztm5J93vxejI/CpK7ddgR8WRlBwc59nYeG6y8m4J/xDyQjgr8CM1AeR\ndL8eXkLBHuHrAAAgAElEQVQWyH82PU/deybLipyLmY0jjONfAf8qUVaTskXf/ux+zPF0WL0zSHRY\nvTO7H3N8XGAqEom0aPY/+0LW26ruv/TWbdrw0+NOrejzq+RXRjO7W9IehLkqactLo6yMGYlEmhcz\ne1xhruIL7sb5BXCImb0s6ULgGUkLCS6Ngwhz5G5UWPBlYCqfryUdQXA1XY6gsCYrjZ5HcCE+n7pW\nt5NdEVhEcKN9pEC2iZLuAqYQXEvHZ1ShA3C/Wy4FnOrhJwLXSppKeNY9S7C2XkZwc/0Twb04YX/g\nUEkLgPeBi8zsE4/3uCtCCwhu118Bt3oYQJaFsFwOBq73ctoQ2ncKYa7fnZLOICjcWdwEbAZMdblv\nNLNrJN1IWCjofeq2WTVwg6SvCO6cAJjZLElnAk8T2nCkmeWVmXC5uwqLoFhlrSQxxGWbCJxVJK+8\nNigkr+8gKOn3EryO7jCzGoCc/nubMDf1IYJyXkNw1YX88f2NwsJJV7sS/RXBqpneymco8KC7wdYQ\nLIGlqCajT5wvgW29Dh8S5hND8KIa57KPo1aBPQkYIukogiXxt2b2gqSxCguTPeLzcJe43z1+Ho8C\nx7rr7mtAlhvz1oQxsYjQznnz7+8ijMlBqbDBhOfGpwSFcsMislDk2XQC4b48ndA2RxTLJ4e7CXPa\nPy1RVpOzRd/+UaGNRCLLHPuffWGTl6laz7OcCNJ1hHk+OxNcdvYlLDiS5Y4XiUQi31vcXbSLmQ1u\nZlGaDUkzzaxLE5c5iOCSfXxTlhspjYKL/Ewzq25mUcpCYR7/lWY2qpLlVFVVWU1NTSWLiEQike8U\nkiaYWVXpmOWtoryTmf0K+NjMzga2AzYpkSYSiUQikUhkmUBSJ0mvE1b+rqhyG4lEIpHKUs5CCMm2\nBV9LWpOwauLalRMpEolEllkmE+Ybf58ptmp2RXDrYHVTlxspi9GEbZFaNGY2h+DuH4lEIpFlnHIU\n3EcUNma/gvDythCIO4tHIpFIAaltYL63mFmTK7iRlouZjW5uGSKRSCTy/aKcRaYG++Ewn5vSvoz9\nMCORSCQSiUQikUgkEmlSSs7B9e05/iDpBjP7ClhV0k+bQLZIJBKJRCKRSCQSiUTKphwX5VuAacBO\nfv4eMIyC7TwikUgkEqkUkr4ws5VKxyyZz7GE/VobNNWmnFWiv0urOkvqB3xjZs+XiDcY+MLMrigz\n3y7AQ2a2laQq4DAzO7ERZB1kZoN8X96rzGxgiWT1zf80M9tT0i+AbmZ2SWPlX4rXx73PC/f/hy8+\nmc9Kq7Zl+703ZrPt1myq4iORSKRB3H/lRN59rXYphtbLiV0O3aKiz69yFNxNzewgSfvx/9k783Ct\nquqPf74MCgLihIYogqQ4oShXcw6HbDBTc6CyFEvN8ueYU2lGaqVSmUNpYgopOYsT5oSChsg8i0Mq\n5oBjiqE4AOv3x14v99yX97zve+FO4Po8z/vcc/bZw9pr77PvWWftvQ/gH3pXo0kUBEEQBI2ApDZm\ndnXlmEGG/qRv5ZY1cFcE/2Zxg34zx8xeJ/Md44bGzO4B7mms/It5bvwbPDb8GRZ9ugSABf/9hMeG\np88sh5EbBEFLpdi4BVi8yHhk6NNA441f1Xwm6FNJ7QADkNQT+LRRpAmCIAhWSSR9X9IESdMk/VVS\naw9fIOk3kqZLekrSBh7eU9I4STMlXZjJR5IGS5rl1wZkrp3lYdMlXeRhoyX9SdIk4GRJgySdnrl2\nscv1nKQ9PLy1lzFR0gxJP86p0zckPSNpsqTLfZ+K4jhDJR2aOV9QQd6+rocZkkZIWtvDT5L0tIff\n7GEdJF3n8k+VdGCJ8vtLGiPpbkkvSrpI0hGeZqakXh6vi6Q7vM4TJe3mXtbjgVO93faQdICk8V7e\nI4X2crbzNnte0rGV2qtIxvv8+Mte1jQvo1O1dSjKs4ekWX48UNKdkh5w2S7JtPPQjGynZvpFjR+v\nJ2luifwHSroy08aXS3rS5Wtww3rc3S8sNW4LLPp0CePufqGhiwqCIGgwio3bAmY06vhVjQf3fOAB\nYCNJw4AvAz9qNImCIAiCVQpJWwIDgN3M7DNJfwGOIO3I3wF4yszOccPjWOBC4DLgKjP7u6QTMtl9\nG+gLbAesB0yU9LiHHQh8yWcarZNJs1rh4/BKU2mztDGznSR9A/gVsC/pf9x8M9tR0urAWEkPmdlL\nmTq1A/4K7GlmL0m6qZ46+XqOvH8HTjSzMZLOd5lOAc4GeprZJ0pfNgA4B3jUzH7oYRMkPWJmHxYV\ntx2wJfBf4EXgWq/zycCJnv9lwKVm9i9J3YEHzWxLSVeTmXrsBvfOZmaSjgHOBH7m5WwL7Exq06mS\nRgK7ULq98jgdOMHMxkrqCHxcjzqUoy+wPfAJ8KykK4D1gW5mto3Xba0y6SvRlbSUawuSZ/f24giS\njgOOA+jevXu9Ml/w30/qFR4EQdDSaczxq6wHV5KA6cBhpIeOEcBO8RH0IAiCoB7sA/QjGTfT/HxT\nv/YpUPB8TgZ6+PFuQMFovCGT1+7ATWa22MzeBMYAO5IM0+vN7COAot3+bykj250lyt4PONJlHQ+s\nC2xWlG4L4MWM0VsvA7eUvJI6A2uZ2RiPMwzY049nAMMlfR9YlJHzbJdzNNAOKGU5TTSzeWb2CfAC\n8JCHz8zUeV/gSs/rHmBNNzCL2Qh4UNJM4Axg68y1u81soZm9AzwG7ER+e+UxFvijpJNcF4W6VlOH\ncowys/lm9jHwNLAJyVDeVNIVkr4GfFBFPnncZWZLzOxpYINSEczsGjOrMbOaLl261CvzjuusXq/w\nIAiClk5jjl9lDVwzM+BhM3vbzO42s7vM7K1GkyYIgiBYFREwzMz6+q935hN0n/n/GkjfWc/OLDIa\nhmKPZpbCK+Rs2SJ5UQvy9jSzh0onr8gi/H+tpFbAasuZz/7An4EdSC8K2rich2Tk7G5mc0qkzb4m\nX5I5X0JtnVuRPLOFvLqZ2QKW5QrgSjPrA/yYZFQXKG6verefb9p0DNCe5Dnfoh51KEc2/WKS5/49\nkmd4NGkq9rV+fWmbUbd+1ebf4PuU7HJgL9qsVveRrc1qrdjlwGVmZwdBELQYNupdemKMRKOOX9Ws\nwZ0maftGkyAIgiBY1RkFHCppfQBJ60japEKascB3/PiITPgTwABfP9mF5OGcADwMHC1pjUIZKyDv\ng8BPJLX1vDaX1KEozrMk718PP19mbakzl+S9BvgW0NaPl5HXzOYD78nXAgM/AMa4YbyxmT0GnAV0\nBjq6nCf6bCtW8H/1Q6Spvnheff3wf0CnTLzOwGt+fFRRHgdKaidpXdLmVBPJb6+SSOplZjPN7GJP\nv0Ve3BVF0npAKzO7AziX9PIA6rZZo21UVR82/9IX2OuILZZ6PDquszp7HbFFbDAVBEGL5sBTd1jG\nyG3dRuw7cKvm2UVZabfJRaQ1KxMlvUB6Cy6Sc3eHvLRBEARBUMDMnpZ0LvCQG2ufAScAL5dJdjLw\nD0lnAXdnwkeQ1nVOJ3kIzzSzN4AH3CibJOlT4H7gF8sp8rWkaa9T3Hh8GzioqE4LJf3Uy/2QZIyV\nYghwt6TppP0sPvT0efIeBVzthu+LwNFAa+BGn8Is0udv3pd0AfAnYIbr9SXgm8tZ55OAP0uaQXo2\neJzk1bwXuF1pA6sTgUHAbZLeAx4FembymEGamrwecIGZvS6pZHtlXgwUc4qkvUie2dmkTxLuspx1\nqkQ34HrXHcDP/e/vgVt9zezIRiq73mz+pS+EQRsEwUrHgac2vcmo2plhRRekKWa2Q6ndCQHMLLbu\nC4IgCD5XKPMdXEkdzWyBG8F/Bp43s0ubVcDPMcp8B7eZRalITU2NTZrUoF9GCoIgWKWRNLmwYWQl\nyq1bEYQhGwRBEAQ5HCvpKNK62qmkXZWDIAiCIGhGyhm4XSSdlnfRzP7YCPIEQRAEQUvmT4UD99aG\nx7blMBe4q7mFCIIgCJqXcgZua9ImFg2+G2AQBEEQrIyY2Z8qxwqaAzObSzJygyAIgs8x5QzceWZ2\nfpNJEgRBEARBEARBEAQrQLnPBIXnNgiCIAiCIAiCIFhpKGfg7tNkUgRB0KBIGi2pxo/vl1T6S9vN\niKS5/h3K+qQZJGlg5vj0RhEuv/yBkjZshHyfXIG0S3XSkEg6XtKRFeK0CH1IGirpUD9e2vebk4bQ\nTbZeReH9Jd23nHkuWBGZSuR3u6RNM+d9JZmkrxXFWyxpmqRZku4tjEmSekha6NemS3pSUm+/1kfS\n0EwePSSNbqy6lKhbo/TvIAiCoHHJNXDN7L9NKUgQBMuHpHJLDTCzb5jZ+00lT2MhqXULKH8g0OAP\nvGa2a0PnuaKY2dVm9vcK0QayEuqjifrSQOqpm+bu4+VQolVR2NZAazN7MRP8XeBf/jfLQjPra2bb\nAP8lfQe5wAt+bTtgGP79YjObCWwkqXsDV6cijXm/Ly/z772X5/fehzlbbsXze+/D/HvvbW6RgiAI\nKjL36KOZs8WWS3/PbLtdo49f5Ty4QRA0IZKOlDTDvRg3eNgBksZLmirpEUkbePggSTdIGgvcIKm9\npJslzZE0AmifyXepp1TSae5BmSXpFA+7SNIJmfiDJJ0uqaOkUZKmSJop6UC/3kHSSJdzlqQBHr6j\ne1+mS5ogqZN7QK7M5H2ff6uyuO53SZosabak4zLhCyT9QdJ0YJcSatvKPXYvSjrJ05xfqJuf/0bS\nye71etxlf1bS1YUHdkn7SRrndb1NUseM7i6WNIX0wF4DDHdvU3tJ/SSNcdkflNTV0432dBMkPSdp\nDw/f2sOmeVtvVqin/5Wkwa7XmRnd9vc8b5f0jKThkpZZRiJpJ6/HVNX1hA2UdKekByQ9L+mSTJof\nuYwTJA0ptJcyHnIlr9xTLvMISWsreRYbWx9V1bsaitryMEm9XB+TJT0haQuPt4HXcbr/dvXw72dk\n/avcGPU+eqlS3x0lqUuObvbxdpkp6TpJq5eSq4To+0qa5Hr7Zol6raN0/8zwNtrWwztKut7LmyHp\nkKJ063lf2d/Pz5A00eP+2sN6KN0rfwdmARsXFX8EcHcmT3kdBgJfkdQupznGAd1yrq0JvJc5vxf4\nTk7cpeXm3Dddle75gue40O+ucp3OLtTVwyvd7+e5jmZJuqbQF/P6d0My/957mffL81j0+utgxqLX\nX2feL88LIzcIghbN3KOPZuG4p+qE2aef8vpZZzfu+GVm8Ytf/Jr5B2wNPAes5+fr+N+1AfnxMcAf\n/HgQMBlo7+enAdf58bbAIqDGz+cC6wH9gJlAB9IO6bOB7f03JiPL06QH2TbAmh62HvBv0tr8Q4Ah\nmfidSd8BfRHY0cPW9PQDgSszce8D+mflKqpve9KD9Lp+bsDhmfSDgIGZ4yeB1V2+d4G2QA9gisdp\nBbwArAv0Bz4GNiXtEv8wcKinfRzo4GnOAs7LyHhmpvzRGb229fK7+PmATBuMzrTVN4BH/PgK4Ag/\nXi3Tfgv87yEuV2tgA+A/QFeXfT6wkddpHLB7CZ2sCbTx432BO/x4oLdPZ6Ad8DKpjTf0Oq7j9Xmi\n0F6e7+l+PAP4sh+fD/ypifSRW++i+2cocGixTEVxittyFLCZH38JeNSPbwFO8ePWrrMtSYZWWw//\nC3Bkpo8W6nBeRn9Z3bQDXgE29/O/Z8qoI1eJej3gdd8MeNXz6g/cl9Hhr/x4b2CaH19caKfCWFLQ\nLalvjQe+4mH7AdeQ7u9WpPt0T9K9tATYOUe+MUCfzPluwCg//gdwSObagoxObwO+5uc9gIXANNK9\nOg/oXpTnvZm4o0vkmXff/Aw4J1Nup6LxprW307aV7vdsOj++ATigXP8u9+vXr5/Vh+f22tue7r3F\nMr/n9tq7XvkEQRA0JaXGreUdv4BJVmFsLfzKTm0MgqDJ2Bu4zczegTpLBDYCbnFP2GrAS5k095jZ\nQj/eE7jc086QNKNEGbsDI8zsQwBJdwJ7mNnlktZXWmvWBXjPzF6R1Bb4raQ9SQ+53UgPjzOBP0i6\nmPSQ/YSkPqSd1ye6DB94GdXW/yRJB/vxxqSH+XeBxcAdZdKNNLNPgE8kvQVsYGZzJb0raXuXd6qZ\nveuyTDCfTinpJtfJx8BWwFiPsxrJkCpwS07ZvYFtgIc9XWvSw3mBO/3vZNKDOZ7vOZI2Au40s+eL\n8twduMnMFgNvShoD7Ah84LK/6rJP8zz/VZS+MzDMPaFGMjoLjDKz+Z7+aWATknE/ptDfJN0GbJ7N\nUFJnYC0zG+NBw0gGSlPogyrrXS23eD4dgV2B2zJ9dHX/uzdwJIC3w3xJPyC9IJro8dsDb3n8JdT2\nkRsz9czSG3jJzJ7z82GkKbqFTw7l9TGAW81sCfC8pBeBLYqu704y8DCzRyWtK2lN0guOpZ5PMyt4\nRduSjPsTMm26n/+m+nlH0j34H+BlM6v7+r2WrsDbmfPvAjf78c0kPRbu3/beft2AOSSDtMALZtYX\nwL2v1wCFNbxvUXmacN59MxG4zseyu8xsmsc/XGmmSBuvw1aklzhQvi32knQmsAbppdBs0osPKN2/\n6+BlHgfQvXv9Zl0vmjevXuFBEAQtncYcv8LADYKWzRXAH83sHqWpvYMy1z5swHJuI3kzv0DtA94R\nJIO3n5l9Jmku0M7MnpO0A8lTcaGkUcCInHwXUXcpxDJTFr1e+wK7mNlHSpvIFOJ97A+teXySOV5M\n7Zh2Lclr+QXgukwcK0pvJK/Vw2ZWvGawQJ6eBcw2s1JTp7OyLZXLzP4haTywP3C/pB+b2aM56fPy\nq5NnERcAj5nZwZJ6kDxL9Um/IjSWPhpS7kJbtgLeLxhVVSBgmJn9vIq4xX2sPnJVk9/y5J9lEckI\n+yrJAwupfr8zs79mI3ofKifbQvxeVZqyfQhwoKRzPM91JXUys//ha3AlrQE8SDLwLy+R5z3A9Znz\ndl5OvTGzx/0F3f7AUEl/JM1SOJ002+Q9pU2ssuNSyfr6dOu/kDy6r0gaVJRumf5dQp5rSMY7NTU1\n9WrHNl27punJJcKDIAhWRhpz/Io1uEHQMniUtC5wXUjr6jy8M/CaHx9VJv3jwPc87TakacrFPAEc\nJGkNSR2Agz0MklH7HZKRW/DOdQbecuN2L5LHD/f0fmRmNwKDgR2AZ4Guknb0OJ2UNr+aC/SV1ErS\nxsBOJeTqTPIaf6S0DnLnMvWslhEkD9COpIfpAjtJ6qm09nYAyRP4FLCbpC+67B0kbV6cofM/oJMf\nPwt0kbSLp2urtOlOLkq7zb5oZpeT1i4Wt9MTwABJrSV1IXnmJ1RV40S2vwysIv5E4MtKa2rb4J7A\nLO71fS+zrvAH1BpGja2PRsFnGLwk6TCXQ5K288ujgJ94eGv3YI8CDpW0voevI2kTj9+KdN9AugcL\n3uVi3fQo9DHq6rASh/n904s0vf7ZoutPkF5GFV4WveP1e5jMRk6S1i5UH/ghsIWkszzsQeCHql17\n3q1Q1wrMAQp12geYYWYbm1kPM9uE5L09OJvAzD4CTgJ+ptIb5O1OmqpcYHPSsoVylLxvvI3eNLMh\npJdeO5Cm8X9I8sxvAHy9TL7ZNiwYs++4npbZ3boxWf/UU1C7uu8H1a4d6596Sk6KIAiC5qf9LjmP\ndK1aNer4FQZuELQAzGw28BtgjNKGSn/0S4NI0ygnA++UyeIqoKOkOaQ1kpNLlDGFtKZvAmn93bVm\nNjVTfifgNTMrzBkZDtRImkmaaviMh/chPTxOA34FXGhmn5IMxitc/odJD4RjSdOqnyZ5a6aUkP0B\noI3LfhHJ4FwhXJ7HSNM7sx7gicCVpAfzl0hTtt8mGYM3KU3tHsey00ALDAWu9rq3Jj3kXux1nkaa\n9lqOw4FZnn4b0lrMLCNIUyWnk156nGlmb1SscC2XAL+TNJUqPJ1m9hrwW1KfGEt6ITG/RNSjgMGu\nn76kPgaNr4/G5AjgRy7rbOBADz+ZNBV1Juk+2srMngbOBR5yHTxMmtoKyVjaSdIs0vTmUroRcDTp\nXp5JmtZ8dZVy/ofUPv8Ejjezj4uuDwL6uVwXUfsi7EJgbaUNkaYDexUS+D3xXWBvST81s4dIa2bH\nuXy3U2vYlWMkaT0wnl/xTI47WHY3ZXzcmZG51kv+mSBSfzwmE30vL6ccefdNf2C63w8DgMvMbDpp\nKvYzpDqPLZPvUGrb8BNgCMnYfpA0ljQZnQ84gK4XnE+bDTcEiTYbbkjXC86n8wEHNKUYQRAE9aLH\n9dcvY+RqtdXY8OKLGnX8KmxeEwRB0OLxaYFzzWxohXitSMb0YYV1ne7dOt3MltmJdmWmWp2USd/R\nzBa4N20EaWOovCnnQRGSFphZx+aWozmQ1J70Imm3CksJljf/1Ume7t3NbJFPmR5qZv0buqympqam\nxiZNmtTcYgRBEKw0SJpsZlV95z48uEEQrFJI2oq04/OonE2LgroMcg/VLJJX+65mlidYSfBN7n5F\n/id/VpTuwNlmtqiR8g+CIAhWQWKTqSAIViZGA++Xi+DTSTctET6aupsurSqMpoJOymFmpzecKJ8/\nPq/e2wJm9mDlWMud9/NA9iXV+6Rpw0EQBEGQSxi4QRCsNLiRGmQInQSfF8wsDNwgCIKgIjFFOQiC\nIAiCIAiCIFglCAM3CIIgCIIgCIIgWCUIAzcIgiAIgiAIgiBYJQgDtwUgabSkGj++X9JazS1TMZLm\nSlqvnmkGSRrYSCI1G5L6S9o1c368pCObU6aGQNKCJihjbk74QElX+nGz61PSQb4bc+H8fEn7NkC+\n2Xv9FyuaX2Pjff2+eqa5SdIMSacWhQ+VdGjDSrg071MkrVFUVn8/rtOWjUUJGRr9fioq/9rGqme2\n3zYHBV1K2lDS7c0oxyBJzbYp28gXR7Lf7fux7bBt2e/2/Rj5YqXPAwdBEDQ/xz54LH2G9Vn663dD\nv0Yfv8LAbWL8W5O5mNk3fCONlRpJrZtbhhWhQjv1B5YauGZ2tZn9vdGFonL/aUoaq42bUp9lOAhY\naiyY2Xlm9kgDl1HSwFVipRybJX0B2NHMtjWzS5uozNbAKcAaOVHqtGVR2oa8n8rJUC+WRy4zO8Z3\nEF+pKVd3M3vdzBrkJcnK9j9q5IsjGfTkIOZ9OA/DmPfhPAY9OSiM3CAIWjTHPngsT73xVJ2wT5d8\nyi+e+EWjjl8r5UNUS0DSke6lmC7pBg87QNJ4SVMlPSJpAw8fJOkGSWOBGyS1l3SzpDmSRgDtM/ku\n9ZRKOk3SLP+d4mEXSTohE3+QpNMldZQ0StIUSTMlHejXO0ga6XLOkjTAw3eU9KSHT5DUKetF8zj3\nFbwgRXW/S9JkSbMlHZcJXyDpD5KmA7sUpRkk6Tr3BLwo6aTMtVL17OH6GeLlPCSpPSUok/4ZScM9\nn9sL3hVJ/SSN8To8KKmrh4+W9CdJk4CTS7WnpB7A8cCpkqZJ2iPTBltImpCRq4ekmeXKLKrHUElX\nS5ok6TlJ3/TwgZLukfQoMMoNoMFe35mFNvW4Z3nYdEkXeVgvSQ942U9I2sLDe0oa5/EvzORRx2sn\n6Uq5J97758WSpgCHlcn7MJdvuqTHc9rtaK/nBGC3or5yuh8fK2mi53NHpg17SXqqILtqPTz9vR1v\nz7S//No+3pYzvS+u7uEXSXpa6X7+vZJ3/lvAYG/jXsp4H1Xi3imqV67+MmEXAe09/+HeV56V9HfS\n92g3lnSV94XZkn6dTZuVN9PXHvWwUZK6Z/rUoZm01ejpax42Bfh2Ttu1k3S963KqpL380kNAN6/X\nHiWS7um6e7FIrjO8nWcU1bWaseYcYEPgMUmPFclZqi0r3ueetuSYpRJjql9bRgZJv/F4T2XyLddW\nV0saD1wiaSel+3Oq66y3x2vt/XSW53Gih2dnB3xN6X/BdEmjSrRfa6UxpKDzH2euLTOGOId5f3+u\n0LZ5/aCMjOd5mbMkXZPpc8Vt0lOlx6YekmZVKHsNSbcq3SMjvG0LeqnzP6qCPJd5n5klaaeMHrYq\n0SfOl//vybT7ycV6XxEum3IZHy/+uE7Yx4s/5rIplzVkMUEQBA1KsXFbYAlLGnf8MrP41fMHbA08\nB6zn5+v437UB+fExwB/8eBAwGWjv56cB1/nxtsAioMbP5wLrAf2AmUAHoCMwG9jef2MysjwNbEz6\n5NOaHrYe8G9AwCHAkEz8zsBqwIskTwvAmp5+IHBlJu59QP+sXEX1bU96GF/Xzw04PJN+EDAwc/wk\nsLrL9y7Qtkw9e7he+nr6W4Hvl2iLcukN2M3jXQec7mU+CXTx8AGZthgN/CWTd7n2PL2onqf78TSg\npx+fBZxbrsyiugwFHiC9eNoMeBVo5+3yakbvhwAPA62BDYD/AF2Br3s5axS10yhgMz/+EvCoH98D\nHOnHJwAL/Lg/cF9Grisz7TgXODNzLS/vmUA3P14rE3+u/+3qcnch9cexeN8r0ue6mbQXAidm+uZ3\n/fj4ItnnAxu5HscBu7seXwE293h/J3nc1gWezbTzWpm2OLSobQ4l594pasdy+htN7b2+IBOnB7AE\n2DkTVmi/1p5u2zLy3gsc5cc/BO7KqUe1etqMNH7cmq1LJp+fUXvfbOFt2c7rMStn3BwK3OblbQX8\n28P3A67x8lp52+5Zz7FmLj4+Zcrqn6OD0VR/n5cas5YZU3NkMOAAP74EOLeKtroPaF3ct4B9gTv8\n+CfA7Zlr62TqVUO6p16hdhxap0RbHJeRZ3VgEtCT/DFkdEYv3wAeqdAP8mRcJyPDDRn9FLdJ3tjU\nA+9fZco+Hfirh29D3f+vxf2mnDxD/HjPTJmDKN0negBTPE4r4AUyY1eR3icBk7p37271oc/QPrbN\n0G2W+fUZ2qde+QRBEDQlpcat5R2/gElW4vmi1C88uMvH3sBtZvYOgJn918M3Ah5U8tqdQTKEC9xj\nZgv9eE/gRk87A5hRoozdgRFm9qGZLQDuBPYws6nA+kprkbYD3jOzV0gPh7+VNAN4BOhGMn5mAl9R\n8krp6ZQAACAASURBVLrtYWbzgd7APDOb6DJ8YGaL6lH/k/wN+FMk43ozD18M3FEm3Ugz+8T19pbL\nV7KeHv8lM5vmx5NJDxFV6cmvvWJmY/34Ro/bm/TQ87CkaSQDdKNMfrdkjsu1Zx63kgxY/O8tVZRZ\nJ72ZLTGz50mG1BYe/nCmn+0O3GRmi83sTWAMsCPpIfh6M/sIUr+U1JE0nfo2L/uvJOMSktf0Jj++\noYq6FbgFoELeY4Ghko4lGWjFfAkYbWZvm9mn1NV7lm2UPMMzgSOobYNdSMYSwD+K0kwws1fNbAnp\nhUMPUhu8ZGbPeZxhpPtwPvAx8DdJ3wY+qlD3Fb13yvGymWVfdR6u5EWdSqr3VmXk3YVaPdxA6iOV\nKKWnLUh6et7/mdyYk3Z3asewZ4CXgc2rKPMu799Pk+5/SAbufl7PKS5DYUxZ3rGmEtXe56XGrFJj\naik+JRmsUHf8KtdWt5nZYj/uTLq3ZgGXZuTal2TALYI6/38K7Aw8bmYv5VyHpO8j/b4dT3pxshkl\nxpBMmjtL1CWvH+TJuJd7VGeS/o9mdZ1tk2rGpryydwdu9vBZ1P3/Wtxvyslzk+fxOLCmavfGWKZP\nmNlc4F1J2+N92czeLRbYzK4xsxozq+nSpUtOtUrzhQ5fqFd4EARBS6cxx68wcBuWK0heqD7Aj0lv\nkwt82IDl3EbyJhUMKEgP/12AfmbWF3gTaOcP9DuQHsoulHRemXwXUbdPtCuOoDRleV9gFzPbjvRQ\nWoj3cebhrBSfZI4Xk7zG5VgmvqSNfdrYNEnHV0hvJc4FzDazvv7rY2b7ZeJk26lce+ZxC8kw2Rww\nN1QrlVlJ5mK56kMr4P1M2X3NbMsy5UHlflCQJTdvMzueZMhvDEyWtO5yyj8U+D9vg1+XkKUUVfcz\nfwDfieRt+ibJg76iVLyPcljaxpJ6kjxR+5jZtsBI0v1cX3mXyqK0rne1zLX63o8NQbZMZf7+LtOH\nvmhmf1vBsaYS1d7ny+ioHmPqZ/6SYGnaesp1AfCYmW0DHED1/agaRJoNUdB5TzN7qEKagi6Wq69I\nagf8heRN7wMMofz/yFJj04qytN9UIU/eWJx331xLmm1zNGnGUINy8g4n06513S7QrnU7Tt6hQWdC\nB0EQNCg7f2HnkuGtaNWo41cYuMvHo6T1SOsCSFrHwzsDr/nxUWXSPw58z9NuQ5p6WMwTwEG+nqgD\ncLCHQTKivkMycgterM7AW2b2ma9F2sTz3xD4yMxuBAaTHsyeBbpK2tHjdFLa2GMu0FdSK0kbkx6k\ni+lM8hp/pLTesnTPrZ5y9VwGM3sl81B2dYX03SUV1gJ/D/iX171LIVxSW0l5ntm89vwf0GnZ6GBm\nL5Aeen5J7cuH+pR5mOu/F7Cppy3mCWCAr3PrQvJETiBNWz5atetU1zGzD4CXJB3mYXLPPyQv63f8\n+IhM/i+T1pmt7l6LfXLqmpu3pF5mNt7MzgPeJhm6WcYDX5a0rqS2wGE5+ugEzPM4WRmfIk0VJVOH\ncjwL9JD0RT//ATDGvdCdzex+4FSgoJu8Ns67d7JUpT/gM69XKdYkPfDPV1q7+XUvL0/eJ6nbloV7\nYC5pGj+ktah55RV4hqSnXn7+3Zx4T3g5+Muc7pTuq9XwIPBDrxuSuklan/qNNbn3ZIVrUP24jctX\nakytppwCeW1VTq6BmfCHgR8X+l3m/0+Bp0hrnXvmXIek858U+p+kzX38XGYMqVCXvH5QSsaCdfaO\nt3W5zaLyxqZqyh4LHO7hWwF9ctJXkqewX8XuwPwynvoCI4CvkWbTPFghbr3Zf9P9GbTrILp26IoQ\nXTt0ZdCug9h/0/0buqggCIIGY8hXhyxj5K7WajV+u8dvG3X8ajE7sq5MmNlsSb8hPSAvJnkWBpLW\n59wm6T2SEdwzJ4urgOslzQHmkKZ8FZcxRdJQkuECcK2l6cmF8jsBr5nZPL8+HLjXp1pNIj2oQvrn\nPljSEuAz4Cdm9qnSxkRXKG3ctJDkKRkLvERa1zuHNF2wmAeA4132Z0kPU8tNXj2VNnNa0fTPAidI\nuo5Up6u87ocCl0vqTLoH/kRau1vMIEq3573A7UobeZ1YIt0tpAffni5jfcr8j9dlTeB4M/tYUnGc\nEaRpjtNJXoUzzewN4AFJfYFJkj4F7ift1HsEcJWkwnrgmz3tycA/JJ0F3J3R6SuSbiWteXyJ1L/z\nyMt7sKTCOs5RHrYUM5snaRBp7ef7pCmypfglyRh+2/8WDIhTgBslnUPqk2UfPl2PR5Pasw0wEbga\nWAe42705Iq2Px+sxRGkTmUMz+eTdOwsycarV3zXADKVpyOcUyTtd0lTSffwK6d7E619K3hNJY8oZ\nrqujPXyIx5/ueio7E8D1dBwwUtJHJCOilNH2F1K7zyR5iQea2Scl+mpFzOwhSVsC4zz9AuD71G+s\nuYbU/183s72KrpVsywyDqG7cLrDMmFqFDFny2qqYS4Bhfm9lt5q8ljQVd4akz0htvHRzQDN729vw\nTiWv/VvAV4ryvhZfN6qk9LeBg8wsbwzJI68fLCOjmV0paQjpvniDdA/mUXJsqrLsv5D09jTp/plN\nifHBzN6vIM/Hfg+2Ja2VLouPDY+RZrWsyOyCXPbfdP8waIMgWOkY8tUhTV5mYWONIGhw3ICZa2ZD\nm6HsHqTNcbZp6rKXFzfU7zOzZvvOY2Mjaa6Z9WiAfNYAFpqZSfoOacOpA1dYwGCVwO+loWY2uplF\nCZoYpc//tPWXNb1Ie1L0trTWv9o8RpM2uptUjzStSC+FD/OlKWWpqamxSZOqzj4IguBzj6TJZlbV\nN9nDgxsEwcpIP+BK9z69TxUeliAIPhesQfpcU1vSLIef1se4XR58KvR9pA0PKxq3QRAEQeMSBm7Q\nmIwmGR9Nju9qudJ4bwHMbGBzy9AE/KkhMjGzJ6hdfxoExdxFWn8cfM4ws/+RPpe0Inn0r2f8p0l7\nJgRBEAQtgDBwg0YjpgcGxZhZgxi4QVAOM7uruWUIgiAIgqB5iF2UgyAIgiAIgiAIglWCMHCDIAiC\nIAiCIAiCVYIwcIMgCFoAkkZLqvHj+/0bui0KSXMlrVfPNIMkDWwkkaqVYa6k9SStJemnVcSvE0/S\nhpIadHdzSQN9p/nC+U6SHpf0rKSpkq4tfI92OfMf6p8nw/PaqkL8erdtS0dSD0mz/LivpG9UkaZO\nPEnfknR2Y8pZNTNuhUu3gUFrpb8zbm1uiYIgCCoz7FswqHPt74L1G338CgM3CIKgifFv8eZiZt8w\ns2bZoK0h8U+2tCTWAioauMXxzOx1Myv1Dd0GQdIGwG3AWWbW28y2J30HuNQ3iEulr9SfjvGNkD7P\n9AUqGrjF8czsHjO7qNGkqpYZt8K9J8H8VwBLf+89KYzcIAhaNsO+BS+NqRu2+BMY8eNGHb/CwA2C\nIFhOJB0paYak6ZJu8LADJI13L9wjbrwUPJk3SBoL3CCpvaSbJc2RNAJon8l3qTdN0mmSZvnvFA+7\nSNIJmfiDJJ0uqaOkUZKmSJop6UC/3kHSSJdzlqQBHr6jpCc9fIKkTu5ZvDKT932S+peo+12SJkua\nLem4TPgCSX+QNB3YpShNR0nXu2wzJB3i4d/1sFmSLi7K6zcu31MZXR7mcadLetzDqpH7IqCXpGmS\nBufpq0S8rCewXaYOUyXtlSn/TkkPSHpe0iUe3tq9qbM8zaklutIJwDAzG1cIMLPbzexN9+yO87Ke\nlNQ7U949kh4FRilxpZIH+BFg/YwusrMDSuq6qJ2W6XMe/kvP/1+SbvI+10vSlEyczbLnmfAv+v0w\n3fXdy2UenNFNoV/2d5lvl/SMpOGS5NcukvS095/fe9hSb7WfLygqezXgfGCAt+mAUnrNibe0X3k/\neNTLHiWpe6b8yz2fF7OyNBijzofPFtYN+2xhCg+CIGipFBu3BWxJo45fsYtyEATBciBpa+BcYFcz\ne0fSOn7pX8DOZmaSjgHOBH7m17YCdjezhZJOAz4ysy0lbQuUMgr6AUcDXyJ903O8pDHALaRPLv3Z\nox4OfBX4GDjYzD5QMpCfknQP8DXgdTPb3/Pt7A/ztwADzGyipDWBoifosvzQzP4rqT0wUdIdZvYu\n0AEYb2Y/87L2zaT5JTDfzPr4tbUlbQhcTPq28XvAQ5IO8p2QOwBPmdk5bjAeC1wInAd81cxeU/2m\ncp8NbGNmfb38Njn6Ko7XI5PHCYCZWR9JW7i8m/u1vsD2wCfAs5KuIBma3cxsG8+rlLzbAMNyZH4G\n2MPMFrkufwsc4td2ALb1dvg20JvUxzYAngauy2ZUQdeFOHl9ro2Xux3QltRfJ5vZC5LmS+prZtM8\n7fUl6jEcuMjMRkhqR3rB/m3X2XbAeqR+9LjH3x7YGngdGAvsJmkOcDCwhd9fVbW9mX0q6Tygxsz+\nz+u5ZrFezeyQEvEGZrK6gvQiYpikHwKXAwf5ta7A7sAWwD3AMlPalV4EHQfQvXv3akSvZf6r9QsP\ngiBo6TTi+BUe3CAIguVjb+A2M3sHwMz+6+EbAQ9KmgmcQXpIL3CPmRWMyD2BGz3tDGBGiTJ2B0aY\n2YdmtgC4k/RQPhVYX2lt6HbAe2b2Cskg+a2kGcAjQDeSsTMT+IqkiyXtYWbzScbQPDOb6DJ8YGaL\n6lH/k5S8tE8BGwObefhi4I6cNPtSa5RjZu8BOwKjzextL3+46wbgU+A+P54M9PDjscBQSccCKzIN\nOk9f5did2nZ7BngZKBi4o8xsvpl9TDIwNwFeBDaVdIWkrwEf1FPGzsBtSh7kS6nbnx7O9Ls9gZvM\nbLGZvQ48WiKvcrrO1m+ZPgfsBtxtZh/7t2bvzaS5FjhaaUr6AOAf2QwldSIZ+SMAPI+PvKyCzG8C\nY1xGgAlm9qqZLQGmkdp+Puklzt/coP+ogu7KUU6veeySqdsNLn+Bu8xsiU8FL9mHzOwaM6sxs5ou\nXbrUU9qN6hceBEHQ0mnE8SsM3CAIgoblCuBK91L+GGiXufZhA5ZzG3AoyaC4xcOOALoA/dz7+CbQ\nzsyeI3n7ZgIXupcqj0XU/d/QrjiC0tTffYFdzGw7YGom3sdmtnh5K1XEZ2ZmfrwYn3VkZseTvOcb\nA5MlrVuN3CUoqa8VkPeTzPFioI0b8dsBo4HjScZgMbNJXtVSXAA85h7gA2i8/rQi3AF8Hfgmyav7\nbgPkWUqXi4CdSN7Rb5LWKUOm7SW1AlarIv9yel1RebWCeS3LPudB2/Z1w9q2T+FBEAQtlZ5fLh2u\nVo06foWBGwRBsHw8ChzmxhWZKcqdgdf8+Kgy6R8HvudptwG2LRHnCeAgSWtI6kCanvmEX7sF+A7J\nyL0tU/ZbZvaZ0trQTTz/DUnToW8EBpOM3WeBrpJ29DidfMruXKCvpFaSNiYZFMV0JnmNP/JpujuX\nqWeWh0lTfPEy1wYmAF9W2uW4NfBdkicvF0m9zGy8mZ0HvE0ydKuR+3/U3bippL5KxMvyBMkwxqcm\ndyfpMk/W9YBWZnYHySjfoUS0K4GjJH0pk+7bSmuOs/1pYF45pP40QGnNb1dgrxJxqtF1Xp8bCxyg\ntAa5I8nABJJHFngQuIoS05Pd4/uqpIO8bqsr7RD9REbmLiRv8oS8Cnq5nc3sfuBU0osDSG1feEHw\nLdIU6mJKtX0pvZZr+ydJ9xykPvBETryGZ9vD4YDLofPGgNLfAy5P4UEQBC2Vo+5Z1shtvToc/NdG\nHb9iDW4QBMFyYGazJf0GGCNpMcmLORAYRJr6+B7JCO6Zk8VVwPW+rnAOaQpucRlTJA2l9qH/Wp+e\nXCi/E/Camc3z68OBe3169CTS+k2APsBgSUuAz4Cf+LrEAcAVvo52IckrOxZ4iTTFdg4l1gaTPGfH\nu+zPkqYpV8OFwJ99Wuhi4NdmdqfSZ1geI3m+RprZ3RXyGSxpM48/Cpju4WXlNrN3JY318v9JWo+6\njL5KxPtzJpu/AFd5mkXAQDP7RMp12nUjtXPhhfLPS8j1pqTvAL+XtD6whGSwPgBcAgyTdC4wsoxO\nRpCmzT8N/AcYVxzBzOZV0nW5Pufrk2eQPN0zSVOGCwwnGcMP5cj3A+Cvks4n9cHDXOZdSO1nwJlm\n9oa/NClFJ+BuX8Mr4DQPH+Lh00k6K+XZfgw4W9I04Hfk67U4XpYTSW15BunFytE5cjYO2x4eBm0Q\nBCsfR93T5EWqdvZXEARBEDQsSt96nWtmQ5tZlBaFb17Uw8wGNbMoVSOpo5ktcO/r48BxZjbFr51O\n8q7+slmFXEmoqamxSZMmNbcYQRAEKw2SJptZTTVxw4MbBEEQBEE1XCNpK9J61WEZ43YE0IvkQQ6C\nIAiCZiUM3CAIgqAxGQ2839xCtECmkdaOrjSY2fdywg9ualmCIAiCII8wcIMgCIJGw8xGN7cMLRH/\nZmwQBEEQBA1M7KIcBEEQBEEQBEEQrBKEgRsEQRAEQRAEQRCsEoSBG5RE0pNVxNlD0mxJ0/wzI/XJ\n/yDfrKRwfr6kfZdH1voiaZDv+Nmk5VaLpIG+82xj5L3A/24o6fblzGOgf1e1cH5tti0bAklzM8e/\nyBz38E+3tGiaun+Xa5NCm69g/mtJ+ulypr1f0loV4sz178XmXR/kuw43KJXaRVKNpMv9eKCkKzPy\nrPAYku3nZeIcL+nI5cl/RcmWLWmopEP9eLSkGj+u2L4eb2dJQyT1lfSNBpazv6T7GiCfBpetIblr\n6mvsdtGj9Dx7JLtd9Ch3TX2tcqIgCIJm5ogh4+hx9silv97n/rPRx69YgxuUxMx2rSLaEcDvzOzG\n5SjiIOA+0jcbMbPzliOPFaa5ym1uzOx14NDlTD4QmAW87nkd00Bi5fEL4LcNkZGkNma2qCHyqkBT\n9++BNG6brAX8lPQN2KpQ+jCszKzFGgyV2sXMJpG+j7vceawoZnZ1Q+SzPH2/mrLr0b5fJ32jti9Q\nA9xfH1maiBYr211TX+Pnd85k4WeLAXjt/YX8/M6ZABy0fbfmFC0IgiCXI4aMY+wL/60T9smiJZx2\na9qGorHGr/DgBiXJePr6+9v62yU9I2m4EscAhwMXSBrucc+QNFHSDEm/zuR1pIdNl3SDpF2BbwGD\n3fvbq8g7sI+kqZJmSrpO0uoevtTL456V0X78Zc9nmqfrVKI+50h6TtK/gN6Z8Gy5F0l62mX9vYd1\nkXSH12uipN08fCdJ47y8JyX19vCtJU1wWWZI2szDv58J/6uk1v4bKmmW1/XUEnIPlHSXpIe9/v8n\n6TQv9ylJ63i8XpIekDRZ0hOStvDwni7nTEkXZvJd6gl1OX7vcsyQdKKHn+d1niXpGm/3Q0kPgMO9\nLu2LvDnf9bJmSbo4258k/cb7wFOSNvDwwzzudEmPl6j/RUB7L2u4B7dW8gTNlvSQfPZAGR0MlXS1\npPHAJWXabqCku70+z0v6VUaOZdqvUK9MnEO9rEr9e0cvd7rnWae/SuooaZSkKa7LAzNtNqe47pXa\nxNNe6mlGSeriYcd6+05X6uNrePgGkkZ4+HSvz0VAL89/sMdb5n53GZ+V9HeSwb2x6t63d3n7zJZ0\nXIn27iBppJc7S9KAEnEGKY0j47ydjs1cy5NpGb1l+kZuu6gKz2BRHnMl/TrTdoU+WM0YNVfSJZ5u\ngqQvZupb8BaPlnSZ5zNL0k4ZvV3n6aZm+sxASfdIehQYlde3PG6dcbq47DL1nytpvXJ6dvYBHgHO\nBwZ4HQYo/368NqOztyX9SonBqh0zs/1jTe87zyrd7608n6skTXKZsv+Xitu7cz1kq2pcbkgGP/js\nUuO2wMLPFjP4wWcbuqggCIIGo9i4LbDEaNTxKwzcoBq2B04BtgI2BXYzs2uBe4AzzOwISfsBmwE7\nkd6C95O0p6StgXOBvc1sO+BkM3syk7avmb1QKEhSO2AoMMDM+pBmGfykgnynAyeYWV9gD2Bh9qKk\nfsB3XK5vADsWZyBpXeBgYGsz2xYoGIOXAZea2Y7AIcC1Hv4MsIeZbQ+cR62H8XjgMpelBnhV0pbA\nANdbX2AxyfvdF+hmZtt4Xa/Pqd82wLdd7t8AH3m544DC1MVrgBPNrJ/ro+Bpuwy4yvOfl5P/cUAP\noK/XvWBIXmlmO5rZNkB74JtmdjvJo3WEt91SXStNkb2Y9C3MvsCOkg7yyx2Ap7wPPA4UjJLzgK96\n+LeKBTOzs4GFXtYRHrwZ8Gcz25r0+ZlDKugAYCNgVzM7jfy2g9R/DwG2BQ5TepGS134lqdC/VwNu\nId0H2wH7UtRfgY+Bg81sB2Av4A+SlFf3cm3idAAmeZoxQMFwv9PbdztgDvAjD78cGOPhOwCzgbOB\nFzz/M/Lu94yMfzGzrc3s5SJZfujtUwOc5Pddlq8Br5vZdt7vHiihYkjtszewC3Ce0pT7SjKV6jNA\n1e1SLe94211F6odQYYzKMN/v1SuBP+XEWcPz+SlwnYedAzxqZjuR+sxgSR382g7AoWb2ZXL6Vqlx\nerlqnqNnpRccn5nZfNI9d4v3pVvIuR/N7Biv54HAO6T/C98mtW2hjQZL6upl7wScSPo/1cvjApxj\nZjWkPvNlSdvmtPeH1crmVDMu10HScW5sT3r77bfrpdjX3y/dZfLCgyAIWjqNOX7FFOWgGiaY2asA\nkqaRjKF/FcXZz39T/bwj6WFnO+A2M3sHwMxKv8qppTfwkpk95+fDgBPIf9gDGAv8UcnDd2dB1gx7\nACPM7COvwz0l8phPevj7m5LHpuC12RfYqta+YE1JHYHOwDAlD60Bbf36OOAcSRu5LM9L2gfoB0z0\nfNoDbwH3AptKugIYCTyUU7/HzOx/wP8kzfd0ADOBbV2eXYHbMnKu7n93o/Zh/gaSAVrMvsDVhemL\nmTbaS9KZwBrAOiRD594S6QvsCIw2s7cBvD32BO4CPqVWp5OBr/jxWGCopFuBO8vkneWlzCdWJgM9\nKugAUh8suD/y2g7gYTN71+W/E9gdWETp9lseegPzzGwigJl9UCKOgN+6cbYE6AZs4NeWqXsVZS4h\nPcwD3EitnrdR8uqvRbpfH/TwvfEHdNfZfElrF+WZd7//B3jZzJ7KkeUkSYVvpm7sad7NXJ9JMrou\nBu4zsydy8rnbDfmFkh4jGTe7l5Gpkt5KtkumL9WHgn4nU2tkVRqjCtyU+XtpuThm9rikNZXWv+4H\nfCvjbW0HdPfjhzP3dF7f2pv6jdN55Ol5P/LHt9z70V943kZ6cfWypFOAm7xfvilpDGnc+YD0f+pF\nT3cTqT/cDhyuNFugDdCVZAAb1bV3ubGi7LhcqqJmdg3pRRw1NTWWo4+SbLhWe14r8TC44Vr12v4i\nCIKgxdCY41d4cINq+CRzvJjSL0ZEWo/b139fNLO/NbAci6jts+0KgWZ2EXAMyfAYK58WWB/cuNuJ\n9ED0TWo9R62AnTP16mZmC4ALSA842wAHFOQxs3+QPJELgfsl7U3SzbBMHr3NbJCZvUd6ATCa5Pkt\neIeLyep/SeZ8CaktWgHvZ/Lva2ZbZqtXX334g+VfSJ6fPsAQMjpfDj4zs4IcS/uQmR1P8hxtDEwu\n4dErRan+WEkHH2aOS7adU6wrI6f9SsRfEf1kOQLoAvRzD9abmbyruRcrUZB5KPB/3r6/pn7yl7vf\nPyyZQOpPepmyi3vNphaX6S+2diAZCRdKylvfmtdOeTI1hN6qpVBWtp9XO0ZZznFenMK5SN78Qt27\nm9kcv55tj3J9qyHI03Nh/W0pyt2PV5NeCDxSRdnL6EVST5L3fB9Ls1NGUr/6lpOt0rjcoJzx1d60\nb9u6Tlj7tq0546u9c1IEQRA0P7v1Kr1io5Vo1PErDNygoXgQ+KF70pDUTdL6wKOkqZ7renihp/8P\nWGYdGvAsySP3RT//AWlaJcBckicNMlMMJfUys5lmdjEwESh+eHwcOEhpbWIn0oNKHQpeWTO7HziV\nZHhC8jqcmInX1w87A4Ut4AZmrm8KvGhmlwN3k97kjwIOdX0gaR1Jm/i0vVZmdgfJyNuhhD4q4t6H\nlyQd5vlLUkH+saTp2ZA/rfZh4MeS2hTko/ZB7h3XTXZDqry2m0CaArie0hrV71LbdiXxthtvaaOe\nt0mGbjGfSWpbInwpFXRQTMm2c77i7dOetFHUWHLaz+O/KWlLpfV+B2fyKde/u0ra0fPqVNB7kXxv\nmdlnkvYCNinOpAR55UEa5wvt9z1qZ190Aua5brN9YxS+LEBpfXbnEvnn3e/l6Ay8Z2YfuYG3c3EE\npWnuH1nauG4w+ffEgZLa+bjSn3TfL49MBappl+WmijGqwIDM33Hl4kjanTSleT6p7ifKXZCSts9J\nm9e38sbpFcZl2hYoeHaL+1LeWHoC0MlfDhR4grRGtrXSWvI9SeMOwE5Kew60IunoX8CaJAN/vtK6\n/6973Lz2rkq25uCg7bvxu2/3odta7RHQba32/O7bfWKDqSAIWjTDj91lGSN39Tat+OPhfRt1/Iop\nykGDYGYPKa1VHOfPWAuA75vZbEm/AcZIWkzy2gwEbgaGSDqJjPFkZh9LOpo01bQN6WGwsJPnr0lT\niC8geT0LnOIPa0tI02j/WSTbFEm3ANNJU0snlqhCJ+Bu91wKOM3DTwL+LGkG6X55nORtvYQ0de1c\nklegwOHADyR9BrwB/NbM/uvxHvKHr89I064XAtd7GMDPc9RbDUcAV3k5bUn6nU5aS/cPSWeRDO5S\nXAtsDsxwuYeY2ZWShpA2CnqDujobClwtaSFpDSQAZjZP0tnAYyQdjjSzvDILDPbpfyIZVtNLxLnG\nZZtCWmuYR54OislrO0gPy3eQ1uzeaGkXXXLa72XS2tT7SMb5JNK0WMjv358qbYxzhRvRC0lezeyn\nfIYD90qa6Xk+U6bOBYZSok2cD0kP/+eS+n/BiPolMN5lH0/tg/3JwDWSfkTywv3EzMZJGqu0Mdk/\nLa3DXeZ+9/h5PAAcL2kOycAoNY25D6lPLCHpOW/9/QxSP1sPuMDSruCvL4dMQNl2aSjKjlEZrmHZ\nLwAAC4JJREFU1vax5hPSC6JSfCxpKqmP/9DDLiAt45jhffQl0kyUYkr2rTLjdEPQD5iamcHxGHC2\n0nKX35F/P55OerlVMIyvBv5K6t/TSR7bM83sDX9hMpG0dvmLXsYIM1viunoGeIX0wqpce1crW7Nw\n0PbdwqANgmClY/ixxY8ljY9q/+cEQdASUPreZ4/MNNjPHZLmmlmPJi5zIFBjZv/XlOUGlVH6LvRc\nMxvqxwvM7PfNK9WKk+3nSt/ErSmsg82JPxo4vfDiZWXAjcN/m9nNzS1LS6KmpsYmTVppmjEIgqDZ\nkTTZ0qaBFQkPbhAEQRAEjYKZXVg5VhAEQRA0HGHgBkHLYxppvfHnmXK7ZjcKZjaUNNU3aHmMJn12\nhlVsZsPSfl7NjAUz69+YwgRBEATBqkAYuEHQwsh8ZuNzi5k1uYEbtFzMbHRzy9AYRD8PgiAIgoYn\ndlEOgiAIgiAIgiAIVglik6kgCIIgCIImRNLbpJ3Yl5f1gNwNyQIgdFSJ0E9lQkflaWr9bGJmXaqJ\nGAZuEARBEATBSoSkSdXuJvp5JXRUntBPZUJH5WnJ+okpykEQBEEQBEEQBMEqQRi4QRAEQRAEQRAE\nwSpBGLhBEARBEAQrF9c0twArAaGj8oR+KhM6Kk+L1U+swQ2CIAiCIAiCIAhWCcKDGwRBEARBEARB\nEKwShIEbBEEQBEHQgpC0saTHJD0tabakkz18HUkPS3re/67t4ZJ0uaR/S5ohaYfmrUHjIqmdpAmS\nprt+fu3hPSWNdz3cImk1D1/dz//t13s0p/xNhaTWkqZKus/PQz8ZJM2VNFPSNEmTPCzuMUfSWpJu\nl/SMpDmSdllZ9BMGbhAEQRAEQctiEfAzM9sK2Bk4QdJWwNnAKDPbDBjl5wBfBzbz33HAVU0vcpPy\nCbC3mW0H9AW+Jmln4GLgUjP7IvAe8COP/yPgPQ+/1ON9HjgZmJM5D/0sy15m1jfzuZu4x2q5DHjA\nzLYAtiP1pZVCP2HgBkEQBEEQtCDMbJ6ZTfHj/5EeLLsBBwLDPNow4CA/PhD4uyWeAtaS1LWJxW4y\nvJ4L/LSt/wzYG7jdw4v1U9Db7cA+ktRE4jYLkjYC9geu9XMR+qmGuMcASZ2BPYG/AZjZp2b2PiuJ\nfsLADYIgCIIgaKH4dNHtgfHABmY2zy+9AWzgx92AVzLJXvWwVRaffjsNeAt4GHgBeN/MFnmUrA6W\n6sevzwfWbVqJm5w/AWcCS/x8XUI/xRjwkKTJko7zsLjHEj2Bt4HrfZr7tZI6sJLoJwzcIAiCIAiC\nFoikjsAdwClm9kH2mqXPYHxuP4VhZovNrC+wEbATsEUzi9RikPRN4C0zm9zcsrRwdjezHUjTa0+Q\ntGf24uf8HmsD7ABcZWbbAx9SOx0ZaNn6CQM3CIIgCIKghSGpLcm4HW5md3rwm4Vpf/73LQ9/Ddg4\nk3wjD1vl8WmTjwG7kKZFtvFLWR0s1Y9f7wy828SiNiW7Ad+SNBe4mTQ1+TJCP3Uws9f871vACNKL\nkrjHEq8Cr5rZeD+/nWTwrhT6CQM3CIIgCIKgBeHrH/8GzDGzP2Yu3QMc5cdHAXdnwo/0nUx3BuZn\nphGuckjqImktP24PfIW0Tvkx4FCPVqyfgt4OBR5179MqiZn93Mw2MrMewHdI9T2C0M9SJHWQ1Klw\nDOwHzCLuMQDM7A3gFUm9PWgf4GlWEv1oFe+/QRD8f3t3H+tlWcdx/P0RSnwgTCtLJ5G05hCPR3Jk\ny1KyHA2jRaa43JTlmpvToaNF6R/aw0bGWkNaW5IPEx+GZMUSaQ1xkA8leYQDZHODmMVmLJJaClP5\n9Md1/eLH4cd5guDwO5/XdsZ9X8/3de9sfHdd93UiIuKoIulCYA3Qzd5vKL9F+Q53CTAW2ApcYXtH\nDYgXAlOB14FZttce9oEfJpI6KAfcjKAs1iyx/W1JZ1JWLE8GuoCrbe+WNAp4gPIt8w5gpu3NR2b0\nh5eki4E5ti/L/OxV5+IX9XYk8JDt70k6hfyOASCpk3JI2TuBzcAs6u8bQ3x+EuBGREREREREW8gW\n5YiIiIiIiGgLCXAjIiIiIiKiLSTAjYiIiIiIiLaQADciIiIiIiLaQgLciIiIiIiIaAsJcCMiIiJi\nWJFkSYub7kdK2i7p1/V+uqS5B9H+bEnHH4qxtmj7NElL/x9t1/bHSdrQdD9Z0mpJf5bUJWmRpOMl\n3S5pTo+6f5H0nkH2e3Fj/gdQZ5GkCQOsc1DvNoa+kUd6ABERERERh9l/gImSjrP9BvBZ4G+NTNvL\ngGUH0f5sYDHlb4IeUra3AZcf6nZbkXQq8Cjlb+M+W9MuB0Yfjv77Yvu6QdQ52HcbQ1xWcCMiIiJi\nOFoOTKvXVwEPNzIkXStpYb2+T9ICSc9I2lwDvP1WHCUtrPVuAk4DVklaVfMulfSspBckPSrpxJo+\nT9ImSeslze85QEkXSXqx/nRJGt28wlr7e0zSCkkvS7qzqe7U2t86SStr2gmS7pH0h9reF/qYoxuA\n+xvBLYDtpbZf7fcsl35/ImmtpI2S7ugxxpckvQDMaEq/XdL9ktZI2ipphqQ7JXXXZ31HLfeUpPMl\njajvaUMtc3PNv6lpfh9pmrPGux0n6cmav1LS2Jre8p3H0SEBbkREREQMR48AMyWNAjqA3/dS9gPA\nhcBlwLzeGrW9ANgGTLE9pW7ZvQ34jO1JwFrgFkmnAF8EzrbdAXy3RXNzgBtsdwKfBN5oUaYTuBI4\nB7hS0hmS3gvcDXzJ9rnAl2vZW4EnbU8GpgA/kHRCL48zEfhjb8/bT7faPp8yzxdJ6qjzfjfweeCj\nwPt71BkPfBqYTlkNX2X7HMocTOtRthM43fbEWubemj4XOK/O7/UtxnUXJYDvAB4EFjTl9fudx9CS\nADciIiIihh3b64FxlNXb5X0U/6XtPbY3AacOsKsLgAnA05JeBK4BPgjsBHYBP5M0g9bbmZ8GflhX\nhU+y/VaLMitt77S9C9hU274AWG17C4DtHbXspcDcOo6ngFHA2AE+T4MHkH5FXaXtAs6mzMdZwBbb\nL9s2JYht9oTtN4FuYASwoqZ3U95bs83AmZLukjQV+FdNXw88KOlqoNXcfRx4qF4/QAloGw7mnccR\nlAA3IiIiIoarZcB8mrYnH8DupmvVf99i3/9LjzpAXQG/td1ZfybY/moNVicDSymrhCt6VrQ9D7gO\nOI4SIJ/Vx9jepvczdkRZ1W2MZaztP/VSfiNldbWVfwDv7pE2Gnhtnw6lD1FWoi+pK6WPc+C5arYb\nwPYe4M0aBAPsoccz2v4ncC4laL8eWFSzpgE/BiYBz0sayPlDrd55HAUS4EZERETEcHUPcIft7kHU\n3QpMkHSspJOAS5ry/s3eg5ieAz4h6cPwv+9gP1K/wx1jezlwMyVA24ek8ba7bX8feJ6y6tkfzwGf\nqsElkk6u6b8BbpSkmn5eH+0sBK6R9LGmMc2oh0+tBqZLGt1IB9bZfrtHG++iHOq1s9b7XE1/CRgn\naXy9v6qfz7afug38GNs/p2wHnyTpGOAM26uAbwBjgBN7VH0GmFmvvwKsGewYYujIKcoRERERMSzZ\n/iv7fnc5kLqvSFoCbAC2ULbfNvwUWCFpW/0O91rgYUnH1vzbKEHwr+q3qAJuadHNbElTKKuWG4En\nKN+G9jW27ZK+BjxWA72/U06K/g7wI2B9Td9CWT0+UDuvSpoJzJf0vjqO1cCKmrcQ+J0k1z72O9XY\n9jpJXZSA9hXKtmts76pjfFzS65TgcrCnM58O3FufCeCblG3NiyWNoczvAtuv1di+4cZa7+vAdmDW\nIPuPIUR7V/sjIiIiIiIijl7ZohwRERERERFtIQFuREREREREtIUEuBEREREREdEWEuBGRERERERE\nW0iAGxEREREREW0hAW5ERERERES0hQS4ERERERER0RYS4EZERERERERb+C9bG8j8VQxWGQAAAABJ\nRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f49ccd1f748>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure()\n",
    "\n",
    "treatments = df['treatmentstring'].unique()\n",
    "\n",
    "for i, t in enumerate(treatments):\n",
    "    idx = df['treatmentstring'] == t\n",
    "    df_plt = df.loc[idx, :]\n",
    "    plt.plot( df_plt['treatmentoffset'], i*np.ones(df_plt.shape[0]), 'o',\n",
    "             label=t)\n",
    "plt.xlabel('Minutes since ICU admission')\n",
    "plt.ylabel('Treatments provided')\n",
    "\n",
    "plt.yticks(np.arange(len(treatments)), treatments)\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Above we can see that most of these treatments were documented as being given twice (or perhaps continuously given over the duration - the interpretation is not clear). Only milrinone and cardioversion were given once around 620 minutes after ICU admission."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Hospitals with data available"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>hospitalid</th>\n",
       "      <th>number_of_patients</th>\n",
       "      <th>number_of_patients_with_tbl</th>\n",
       "      <th>data completion</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>106</th>\n",
       "      <td>264</td>\n",
       "      <td>5237</td>\n",
       "      <td>4857</td>\n",
       "      <td>92.743937</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>134</th>\n",
       "      <td>338</td>\n",
       "      <td>4277</td>\n",
       "      <td>4217</td>\n",
       "      <td>98.597148</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>90</th>\n",
       "      <td>243</td>\n",
       "      <td>4243</td>\n",
       "      <td>4089</td>\n",
       "      <td>96.370493</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>200</th>\n",
       "      <td>443</td>\n",
       "      <td>3656</td>\n",
       "      <td>3597</td>\n",
       "      <td>98.386214</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>122</th>\n",
       "      <td>300</td>\n",
       "      <td>3617</td>\n",
       "      <td>3542</td>\n",
       "      <td>97.926458</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>80</th>\n",
       "      <td>208</td>\n",
       "      <td>3650</td>\n",
       "      <td>3425</td>\n",
       "      <td>93.835616</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>184</th>\n",
       "      <td>420</td>\n",
       "      <td>4679</td>\n",
       "      <td>3279</td>\n",
       "      <td>70.079077</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>206</th>\n",
       "      <td>458</td>\n",
       "      <td>3701</td>\n",
       "      <td>3240</td>\n",
       "      <td>87.543907</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>71</th>\n",
       "      <td>199</td>\n",
       "      <td>4240</td>\n",
       "      <td>3151</td>\n",
       "      <td>74.316038</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>177</th>\n",
       "      <td>411</td>\n",
       "      <td>3199</td>\n",
       "      <td>2908</td>\n",
       "      <td>90.903407</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     hospitalid  number_of_patients  number_of_patients_with_tbl  \\\n",
       "106         264                5237                         4857   \n",
       "134         338                4277                         4217   \n",
       "90          243                4243                         4089   \n",
       "200         443                3656                         3597   \n",
       "122         300                3617                         3542   \n",
       "80          208                3650                         3425   \n",
       "184         420                4679                         3279   \n",
       "206         458                3701                         3240   \n",
       "71          199                4240                         3151   \n",
       "177         411                3199                         2908   \n",
       "\n",
       "     data completion  \n",
       "106        92.743937  \n",
       "134        98.597148  \n",
       "90         96.370493  \n",
       "200        98.386214  \n",
       "122        97.926458  \n",
       "80         93.835616  \n",
       "184        70.079077  \n",
       "206        87.543907  \n",
       "71         74.316038  \n",
       "177        90.903407  "
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "query = query_schema + \"\"\"\n",
    "with t as\n",
    "(\n",
    "select distinct patientunitstayid\n",
    "from treatment\n",
    ")\n",
    "select \n",
    "  pt.hospitalid\n",
    "  , count(distinct pt.patientunitstayid) as number_of_patients\n",
    "  , count(distinct t.patientunitstayid) as number_of_patients_with_tbl\n",
    "from patient pt\n",
    "left join t\n",
    "  on pt.patientunitstayid = t.patientunitstayid\n",
    "group by pt.hospitalid\n",
    "\"\"\".format(patientunitstayid)\n",
    "\n",
    "df = pd.read_sql_query(query, con)\n",
    "df['data completion'] = df['number_of_patients_with_tbl'] / df['number_of_patients'] * 100.0\n",
    "df.sort_values('number_of_patients_with_tbl', ascending=False, inplace=True)\n",
    "df.head(n=10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div class=\"vega-embed\" id=\"0fba70ad-406c-4f8e-be3a-c75b876578d1\"></div>\n",
       "\n",
       "<style>\n",
       ".vega-embed svg, .vega-embed canvas {\n",
       "  border: 1px dotted gray;\n",
       "}\n",
       "\n",
       ".vega-embed .vega-actions a {\n",
       "  margin-right: 6px;\n",
       "}\n",
       "</style>\n"
      ]
     },
     "metadata": {
      "jupyter-vega3": "#0fba70ad-406c-4f8e-be3a-c75b876578d1"
     },
     "output_type": "display_data"
    },
    {
     "data": {
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hYRsSkIAEJKDgOQa6SGBRgne5Im4fBA4tgrdd+feGAvI+wC2BC4Bzi+zlj04H9gDOXwm4FbwuDkNjloAEJFAvAQWv3twY2eoEFiV4o4jGBe/qwIllyjZ/vidwCPDT8vOTykk5Jz8/U8FzaEtAAhKQQNsEFLy2CXv9NgjULHi3BQ4qlbqI30jwTi4/P2vLli1HLC0tHbkczMaNG9tg5TUlIAEJSGCABA47btVl31XSOOaA3diwYcOi7+9VshlSUIseAOMVvEsAZwE7lQTsD9yiCN55wHHl53kgIw9mZOp2q8Mp2iENX/sqAQlIoH0CVvDaZ2wLsydQk+Cld+8Hngl8HHgH8ALgF8BRwD7ALsCxZfp2RRoK3uwHiVeUgAQkMGQCCt6Qs9/dvi9K8PLk7KOBawPfBr4M3Au4UXlK9lLAR4DHFbSbgX2BC4EDgdNWQ67gdXcwGrkEJCCBGgkoeDVmxZi2RWBRgretuKb+cwVvanSeKAEJSEACKxBQ8BwWXSSg4HUxa8YsAQlIQAJzI6DgzQ21Dc2QgII3Q5heSgISkIAE+kdAwetfTofQIwVvCFm2jxKQgAQkMDUBBW9qdJ64QAIK3gLh27QEJCABCdRPQMGrP0dGuDUBBc9RIQEJSEACEliDgILn8OgiAQWvi1kzZglIQAISmBsBBW9uqG1ohgQUvBnC9FISkIAEJNA/Agpe/3I6hB4peEPIsn2UgAQkIIGpCSh4U6PzxAUSUPAWCN+mJSABCUigfgIKXv05MsKtCSh4jgoJSEACEpDAGgQUPIdHFwkoeF3MmjFLQAISkMDcCCh4c0NtQzMkoODNEKaXkoAEJCCB/hFQ8PqX0yH0SMEbQpbtowQkIAEJTE1AwZsanScukICCt0D4Ni0BCUhAAvUTUPDqz5ERbk1AwXNUSEACEpCABNYgoOA5PLpIQMHrYtaMWQISkIAE5kZAwZsbahuaIQEFb4YwvZQEJCABCfSPgILXv5wOoUcK3hCybB8lIAEJSGBqAgre1Og8cYEEFLwFwrdpCUhAAhKon4CCV3+OjHBrAgqeo0ICEpCABCSwBgEFz+HRRQIKXhezZswSkIAEJDA3Agre3FDb0AwJKHgzhOmlJCABCUigfwQUvP7ldAg9UvCGkGX7KAEJSEACUxNQ8KZG54kLJKDgLRC+TUtAAhKQQP0EFLz6c2SEWxNQ8BwVEpCABCQggTUIKHgOjy4SUPC6mDVjloAEJCCBuRFQ8OaG2oZmSEDBmyFMLyUBCUhAAv0joOD1L6dD6JGCN4Qs20cJSEACEpiagII3NTpPXCABBW+B8G1aAhKQgATqJ6Dg1Z8jI9yagILnqJCABCQgAQmsQUDBc3h0kYCC18WsGbMEJCABCcyNgII3N9Q2NEMCCt4MYXopCUhAAhLoHwEFr385HUKPFLwhZNk+SkACEpDA1AQUvKnReeICCSh4C4Rv0xKQgAQkUD8BBa/+HBnh1gQUPEeFBCQgAQlIYA0CCp7Do4sEFLwuZs2YJSABCUhgbgQUvLmhtqEZElDwZgjTS0lAAhKQQP8IKHj9y+kQeqTgDSHL9lECEpCABKYmoOBNjc4TF0hAwVsgfJuWgAQkIIH6CSh49efICLcmoOA5KiQgAQlIQAJrEFDwHB5dJKDgdTFrxiwBCUhAAnMjoODNDbUNzZBAbYK3D/A04NfAT4AHAr8Ejgb2Bi4CDgZOXY3B5s2blzZt2lRbv2aYMi8lAQlIQALzJKDgzZO2bc2KQG0i9CUgknce8Hzg88DXgcOB/YCdgeOB3RW8WQ0BryMBCUhAAmsRUPAcH10kUJvgfRR4JBDROwF4K7ArcG75/zA+HdgDOH8l4FbwujgMjVkCEpBAvQQUvHpzY2SrE1iP4F0a2B743gwBR+ZOAr4PfAO4M/AS4MTy8zT1QeAQ4EwFb4bkvZQEJCABCaxIQMFzYHSRQFPB2x+4DbAZ+C/gasChwItm1PlTgIcBXwZeCHymTMeOC97JwEHAWVu2bDliaWnpyOVtb9y4cUbheBkJSEACEhg6gcOOW3XZd5VojjlgNzZs2ND0/l5lXwxqegJNB8A5wFHANYGHAM8Gngpce/oQ/nDmpYAzgJ3KT+4B7At8p6zJO678PJ/ZDbjACt4MqHsJCUhAAhJYk4AVPAdIFwk0FbwLgasC7wI+BzwF+CkQOZvF8TXgdsC3i0j+GPjP8t95+GIX4Fhgz9Uacw3eLNLgNSQgAQlIYERAwXMsdJFAU8HLww95svU+wL2K7GWKdFR1Wy+DSNwRwK+AH5bp2p+VKeFU8yKYBwKnKXjrRe35EpCABCQwCQEFbxJKfqY2Ak0FLwL2nLL+7hHAK4APlX9X0TcreFWkwSAkIAEJ9IaAgtebVA6qI00FbzmciwO/rYmYgldTNoxFAhKQQPcJKHjdz+EQezCp4OUp1tWO7crDEFXwU/CqSINBSEACEugNAQWvN6kcVEcmFbysu8uRit0Nga+W/75e2TZs1Z0l5k1TwZs3cduTgAQk0G8CCl6/89vX3k0qeKP+v6VsIfbx8oO8iPgBwP1rAaTg1ZIJ45CABCTQDwIKXj/yOLReNBW8XwC3L1W7sLot8E7gyrWAU/BqyYRxSEACEugHAQWvH3kcWi+aCt4HgDsAXwFy7o2AT5Z311XBTsGrIg0GIQEJSKA3BBS83qRyUB1pKng7AE8qO0kEVLYSe+6M96NdVwIUvHXh82QJSEACElhGQMFzSHSRQFPBexnwdOC7tXZWwas1M8YlAQlIoJsEFLxu5m3oUTcVvFOALcDbagWn4NWaGeOSgAQk0E0CCl438zb0qJsK3vuAvYCzgAvG4O1RC0gFr5ZMGIcEJCCBfhBQ8PqRx6H1oqngfQS4aAVIe9cCTsGrJRPGIQEJSKAfBBS8fuRxaL1oKngjPqPzlmoDpuDVlhHjkYAEJNBtAgpet/M31OibCt41gDxocUcgcvdu4GDg+7UAVPBqyYRxSEACEugHAQWvH3kcWi+aCl5earxLEbucux/wMeC+tYBT8GrJhHFIQAIS6AcBBa8feRxaL5oK3o+B7Dt7ZgF1Y+CjwFVrAafg1ZIJ45CABCTQDwIKXj/yOLReNBW8bwMPArKjRY6/Bf4dyNRtFYeCV0UaDEICEpBAbwgoeL1J5aA60lTw/gU4DPgicDFgZyA/e2It1BS8WjJhHBKQgAT6QUDB60ceh9aLpoJ3SeAxwJ2A3wHvAY4FflMLOAWvlkwYhwQkIIF+EFDw+pHHofWiqeCFz9XK3rOXAHYEvlETNAWvpmwYiwQkIIHuE1Dwup/DIfagqeDdBzgO2B64UhG9PEH71lrgKXi1ZMI4JCABCfSDgILXjzwOrRdNBe9s4B3A44CLA5uBuwPXrwWcgldLJoxDAhKQQD8IKHj9yOPQetFU8LL/7E2AcwqoawNfKBW9KtgpeFWkwSAkIAEJ9IaAgtebVA6qI00F771ApC4PV+TcuwKp6uWhiyoOBa+KNBiEBCQggd4QUPB6k8pBdaSp4F0L+DfgDkXwsovFw4D/qYWagldLJoxDAhKQQD8IKHj9yOPQetFU8MLn0sB1gdPLOrxf1wRNwaspG8YiAQlIoPsEFLzu53CIPWgqeNm54rXAFYroZar2hcBJtcBT8GrJhHFIQAIS6AcBBa8feRxaL5oKXqp2xwNPB64IHF62LrtRLeAUvFoyYRwSkIAE+kFAwetHHofWi6aCl6dorwz8oLwHLw9cfAm4fC3gFLxaMmEcEpCABPpBQMHrRx6H1oumgvch4EJgL+ClwH7AucDf1AJOwaslE8YhAQlIoB8EFLx+5HFovWgqeNcBTgBuW/af/SRwAPC1WsApeLVkwjgkIAEJ9IOAgtePPA6tF00Fb8TnUsBFwG+BywC/rAWcgldLJoxDAhKQQD8IKHj9yOPQejGp4P0psAW4WVlz9yTgu8BtSkXPrcqGNnLsrwQkIIGBEFDwBpLonnVzUsF7M3BP4HPADYHPlv9+VJmeVfB6NjDsjgQkIAEJ/C8BBc+R0EUCkwrej4CnAi8GdgVOLWvwngM8szx4UUX/naKtIg0GIQEJSKA3BBS83qRyUB2ZVPCWypOzHykvOM6au7sD76qNloJXW0aMRwISkEC3CSh43c7fUKNfj+DdCjilNnAKXm0ZMR4JSEAC3Sag4HU7f0ONvongnQP8HMg52bni62NPz964FoAKXi2ZMA4JSEAC/SCg4PUjj0PrxaSC94ltgNmzFnAKXi2ZMA4JSEAC/SCg4PUjj0PrxaSC1xkuCl5nUmWgEpCABDpBQMHrRJoMchkBBc8hIQEJSEACEliDgILn8OgiAQWvi1kzZglIQAISmBsBBW9uqG1ohgQmFbzsN3sc8BjgBWWLshmG8YdLbQ+8CdgJ+DJwX+DXwNHA3mV7tIPLe/hWbN8p2jbS4jUlIAEJDJeAgjfc3He555MK3i+ABwNvBO5dXnI83u8TZwQhL04+D/hX4BnAe4HtgMPzMnFgZ+B4YPfV2lPwZpQJLyMBCUhAAr8noOA5ELpIYFLB+ziw1pOyk15nW4y+BNwaOH/sg0cC55Y9b/Pj04E9ln3mDx9X8LaF2D+XgAQkIIEmBBS8JrT8bC0EJhWzy5TqWbYou32ZNh3vw6xeeJx37b2sTMeeATwWOAZIhfCk0uAHgUOAM1eCqODVMrSMQwISkEA/CCh4/cjj0HoxqeCNuFypyN3NgGxfdtrYy45nwe4C4C5AKoZZ6/cV4CbLBO9k4CDgrC1bthyxtLSUCt8fHRs3bpxFLF5DAhKQgAQkwGHHpbbRneOYA3Zjw4YNTe/v3emgkU5EoOkAyPTp24Crlat/s+xJ+7mJWtv2h84CblAe4rgbcCfgu2VdXh7yyJHK3m5AZHCrwwretiH7CQlIQAISmJyAFbzJWfnJegg0FbxPAz8AXl22LHsocCngtjPq0guB9wPvBDYD3wAij0cB+wC7AMeutR5QwZtRJryMBCQgAQn8noCC50DoIoGmgpe9aK9TKmrp7zXLNOoVZtT5HYDXAPl39rp9UJkCjuztC1wIHFimhldsUsGbUSa8jAQkIAEJKHiOgc4SaCp4ebDhVUAqbRcDDgUeAFyvFgIKXi2ZMA4JSEAC/SBgBa8feRxaL5oKXqZk8x660ZEHLR4CvLIWcApeLZkwDglIQAL9IKDg9SOPQ+tFU8ELn7xkONOlvysvIv5MTdAUvJqyYSwSkIAEuk9Awet+DofYg2kEr2pOCl7V6TE4CUhAAp0joOB1LmUGXJ6E7RUIBa9X6bQzEpCABBZOQMFbeAoMYAoCVvCmgOYpEpCABCQwHAIK3nBy3aeeNhW87AN7V+C/a4VgBa/WzBiXBCQggW4SUPC6mbehR91U8LIvbHaQGP17xO9XtYBU8GrJhHFIQAIS6AcBBa8feRxaL5oKXuTucius3Wt6ndY4K3itofXCEpCABAZJQMEbZNo73+mmYnYkcNEKvX5WLSQUvFoyYRwSkIAE+kFAwetHHofWi6aCFz67ArcEXgzcCMi6vGoOBa+aVBiIBCQggV4QUPB6kcbBdaKp4D0J2AJkzd1lgE8B7wT+uRZyCl4tmTAOCUhAAv0goOD1I49D60VTwfsmcA/gZOBKwJ3K1mXXqAWcgldLJoxDAhKQQD8IKHj9yOPQetFU8H4IXBf4ehG82wDvAq5SCzgFr5ZMGIcEJCCBfhBQ8PqRx6H1oqngvQK4M3BV4EvAjYFXAw+pBZyCV0smjEMCEpBAPwgoeP3I49B60VTwsu7uycDeZR3eR4GjgZ/XAk7BqyUTxiEBCUigHwQUvH7kcWi9aCp44bM9cAPgd8BXapK7BKfgDW0I218JSEAC7RJQ8Nrl69XbIdBU8B4GHAtctoRzPnAg8IZ2wmt+VQWvOTPPkIAEJCCB1QkoeI6OLhJoKnjfA/6zCF3OvS+wC+BTtF3MvjFLQAISkMA2CSh420TkByok0FTw8pqUWwHfKH3ZEVM62f4AACAASURBVPgskH9XcVjBqyINBiEBCUigNwQUvN6kclAdmVTw8r67HH9TXpOSp2mXgAcBZ5YHL6oAp+BVkQaDkIAEJNAbAgpeb1I5qI5MKniRubWOSa/TOlwFr3XENiABCUhgUAQUvEGluzednVTM9lyjx9sBH66FiIJXSyaMQwISkEA/CCh4/cjj0HoxqeCNuFwcyO4VfwZcbAyWT9EObeTYXwlIQAIDIaDgDSTRPetmU8F7J3C3FRg0vU5rGK3gtYbWC0tAAhIYJAEFb5Bp73ynm4rZL4FDgVOA3471/oxaSCh4tWTCOCQgAQn0g4CC1488Dq0XTQXvNcCrgPfXCkrBqzUzxiUBCUigmwQUvG7mbehRNxW8VO+eD/y6/DPid6VaQCp4tWTCOCQgAQn0g4CC1488Dq0XTQXvZ8AXgc8sm6J9TC3gFLxaMmEcEpCABPpBQMHrRx6H1oumgvfl8hTtT2oFpeDVmhnjkoAEJNBNAgpeN/M29KibCt6LgLwT7+RlU7SbagGp4NWSCeOQgAQk0A8CCl4/8ji0XjQVvN8B+Wf5cYlawCl4tWTCOCQgAQn0g4CC1488Dq0XTQUvn9/WtmULZajgLRS/jUtAAhLoHQEFr3cpHUSHmgreE1agkms8txZaCl4tmTAOCUhAAv0goOD1I49D60VTwVupepcXHjtFO7SRY38lIAEJDISAgjeQRPesm00Fb/x9d5cBHgzk1SkvqIWLFbxaMmEcEpCABPpBQMHrRx6H1oumgrecz47A6cCVawGn4NWSCeOQgAQk0A8CCl4/8ji0XjQVvLePAbo4cAvgQmCnWsApeLVkwjgkIAEJ9IOAgtePPA6tF00F7/NjgLIe79vAs4BP1QJOwaslE8YhAQlIoB8EFLx+5HFovWgqeNXzUfCqT5EBSkACEugUAQWvU+ky2EJgUsE7cRvE9quFqIJXSyaMQwISkEA/CCh4/cjj0HoxreBlejZP0e4FXAyY9Dqt81XwWkdsAxKQgAQGRUDBG1S6e9PZacQsYvdoIPvP/rqswZv1a1IOAx4I7FpIHw3sDVwEHAyculoGFLzejE07IgEJSKAKAgpeFWkwiIYEmghenprNe++eAWwPPK/8k/fgzfLIq1deA1yxCN7tgMOBTAPvDBwP7K7gzRK515KABCQggdUIKHiOjS4SmFTw7gn8E7ABeGmp2n2/pQ6/FnhheXlyKnhHAucCJ5T28t69PYDzV2rfCl5LWfGyEpCABAZKQMEbaOI73u1JBS9r7vLPB4HvrrDm7gEz4rAPcNcy/fuJUsF7CZCHPE4qbSSGQ4AzFbwZUfcyEpCABCSwKgEFz8HRRQKTCl5ka61jzxl0/lLA+4C7Ab8BVhO8k4GDgLO2bNlyxNLSUip8f3Rs3LhxBuF4CQlIQAISkAAcdtyqy76rxHPMAbuxYcOGSe/vVfbBoNZPoKYBcJuyvu4npUKY9XaZrv0WcB5wXOnuGcBuwAVW8NY/ALyCBCQgAQmsTcAKniOkiwRqErxxfpceq+DdGjgKyPTtLsCxwKoVQ9fgdXEYGrMEJCCBegkoePXmxshWJ9AFwUv0m4F9y763BwKnrdYlBc/hLgEJSEACsySg4M2SpteaF4FaBW/q/it4U6PzRAlIQAISWIGAguew6CIBBa+LWTNmCUhAAhKYGwEFb26obWiGBBS8GcL0UhKQgAQk0D8CCl7/cjqEHil4Q8iyfZSABCQggakJKHhTo/PEBRJQ8BYI36YlIAEJSKB+Agpe/Tkywq0JKHiOCglIQAISkMAaBBQ8h0cXCSh4XcyaMUtAAhKQwNwIKHhzQ21DMySg4M0QppeSgAQkIIH+EVDw+pfTIfRIwRtClu2jBCQgAQlMTUDBmxqdJy6QgIK3QPg2LQEJSEAC9RNQ8OrPkRFuTUDBc1RIQAISkIAE1iCg4Dk8ukhAweti1oxZAhKQgATmRkDBmxtqG5ohAQVvhjC9lAQkIAEJ9I+Agte/nA6hRwreELJsHyUgAQlIYGoCCt7U6DxxgQQUvAXCt2kJSEACEqifgIJXf46McGsCCp6jQgISkIAEJLAGAQXP4dFFAgpeF7NmzBKQgAQkMDcCCt7cUNvQDAkoeDOE6aUkIAEJSKB/BBS8/uV0CD1S8IaQZfsoAQlIQAJTE1DwpkbniQskoOAtEL5NS0ACEpBA/QQUvPpzZIRbE1DwHBUSkIAEJCCBNQgoeA6PLhJQ8LqYNWOWgAQkIIG5EVDw5obahmZIQMGbIUwvJQEJSEAC/SOg4PUvp0PokYI3hCzbRwlIQAISmJqAgjc1Ok9cIAEFb4HwbVoCEpCABOonoODVnyMj3JqAgueokIAEJCABCaxBQMFzeHSRgILXxawZswQkIAEJzI2Agjc31DY0QwIK3gxheikJSEACEugfAQWvfzkdQo8UvCFk2T5KQAISkMDUBBS8qdF54gIJKHgLhG/TEpCABCRQPwEFr/4cGeHWBBQ8R4UEJCABCUhgDQIKnsOjiwQUvC5mzZglIAEJSGBuBBS8uaG2oRkSUPBmCNNLSUACEpBA/wgoeP3L6RB6pOANIcv2UQISkIAEpiag4E2NzhMXSEDBWyB8m5aABCQggfoJKHj158gItyag4DkqJCABCUhAAmsQUPAcHl0koOB1MWvGLAEJSEACcyOg4M0NtQ3NkICCN0OYXkoCEpCABPpHQMHrX06H0CMFbwhZto8SkIAEJDA1AQVvanSeuEACCt4C4du0BCQgAQnUT0DBqz9HRrg1AQXPUSEBCUhAAhJYg4CC5/DoIgEFr4tZM2YJSEACEpgbAQVvbqhtaIYEahO8XYGXApcETgMeDPwWOBrYG7gIOBg4dTUGmzdvXtq0aVNt/ZphyryUBCQgAQnMk4CCN0/atjUrArWJUMTtocAXgdcCbwF+ABwO7AfsDBwP7K7gzWoIeB0JSEACEliLgILn+OgigdoEb0fgvAJyC3AWcE3gXOCE8vPTgT2A81cCbgWvi8PQmCUgAQnUS0DBqzc3RrY6gdoEbxTpVYGPAnsBRwEnAieVP/wgcAhwpoLn0JaABCQggbYJKHhtE/b6bRCoUfAidxG6pwMfAF6yTPBOBg5KdW/Lli1HLC0tHbkczMaNG9tg5TUlIAEJSGCABA47btVl31XSOOaA3diwYUON9/cqefU1qNoGwGWL1D0TeG+BHtHLtO1x5f/PAHYDLrCC19dhab8kIAEJ1EPACl49uTCSyQnUJnjHAJ8BXj3WhVuXadp9gF2AY4E9V+uia/AmT76flIAEJDBvAvttev1Wsy7zjqFJeydu3v9IBa8JMT9bC4HaBO/C8mDFiE9ELw9bbAb2BfLnB5ZXqKzIUMGrZWgZhwQkIIGtCXRNlk7cfN8/6VrMTtH6mxcCtQneurOi4K0boReQgAQk0BqBrsmSgtfaUPDCLRNQ8FoG7OUlIAEJSOD/E1Dw2h8NVvDaZ9yFFhS8LmTJGCUgAQn0hICC134iFbz2GXehBQWvC1kyRglIQAI9IaDgtZ9IBa99xl1oQcHrQpaMUQISkEBPCCh47SdSwWufcRdaUPC6kCVjlIAEJNATAgpe+4lU8Npn3IUWeil4n/jJtbvA/g8x5imtTgVssBKQgASmJKDgTQmuwWkKXgNYPf5o78Qir0lR8Ho8Yu2aBCTQaQIKXvvpU/DaZ9yFFhS8CrJkBa+CJBiCBCQwFwIKXvuYFbz2GXehBQWvgiwpeBUkwRAkIIG5EFDw2ses4LXPuAstKHgVZEnBqyAJhiABCcyFgILXPmYFr33GXWhBwasgSwpeBUkwBAlIYC4EFLz2MSt47TPuQgsKXgVZUvAqSIIhSEACcyGg4LWPWcFrn3EXWlDwKsiSgldBEioOYb9Nrz+y4vC2Cu3Ezft3Kt4usV0eaxfHhoLX/ohT8Npn3IUWFLwKsqTgVZCEikPo4g2xYpy9Cq2LY8OY2x+CCl77jLvQgoJXQZYUvAqSUHEIXbwhVoyzV6F1cWwYc/tDUMFrn3EXWlDwKsiSgldBEioOoYs3xIpx9iq0Lo4NY25/CCp47TPuQgsKXgVZUvAqSELFIXTxhlgxzl6F1sWxYcztD0EFr33GXWhBwasgSwpeBUmoOIQu3hArxrlqaD6w0H7W8l3XxfHctZgVvPbHchdaUPAqyJKCV0ESKg6hazeXro7nLnI25vZ/cbsopQpe++OiCy0oeBVkqas3xArQDSKELt7Eu5iYLnI25vZHmoLXPmNbaIeAgtcO10ZXVfAa4Rrch7t4E+9ikrrI2ZjbH2kKXvuMbaEdAgpeO1wbXVXBa4RrcB/u4k28i0nqImdjbn+kKXjtM7aFdggoeO1wbXRVBa8RrsF9uJs38e7tvtFNzm9Y6tIvRBdlqYsxuwavS78V7cWq4LXHduIrK3gToxrkBxWP9tPexZu4Mbc/LtJCFzkrePMZG7W3ouBVkCEFr4IkVByCgtd+crp4Ezfm9seFgjcfxrbSDgEFrx2uja6q4DXCNbgPK3jtp1xZap9xV2Wpi2PDCt58xnPtrSh4FWRIwasgCRWHoOC1n5wu3sSNuf1x0VUpVfDmMzZqb0XBqyBDCl4FSag4BAWv/eQoS+0z7qosdXFsKHjzGc+1t6LgVZAhBa+CJFQcgoLXfnK6eBM35vbHRVelVMGbz9iovRUFr4IMKXgVJKHiEBS89pOjLLXPuKuy1MWxoeDNZzzX3oqCV0GGFLwKklBxCApe+8np4k3cmNsfF12VUgVvPmOj9lYUvAoypOBVkISKQ1Dw2k+OstQ+467KUhfHhoI3n/FceysKXgUZUvAqSELFISh47SenizdxY25/XHRVShW8+YyN2ltR8CrIkIJXQRIqDkHBaz85ylL7jLsqS10cGwrefMZz7a0oeBVkSMGrIAkVh6DgtZ+cLt7Ejbn9cdFVKVXw5jM2am9FwasgQ139oq4A3SBCUPDaT3NXfwcdG46NlQgoeO2Piy60oOBVkKWu3lwqQDeIELyJt5/mrv4OOjYcGwpe+2Ogqy0oeBVkrqs3lwrQNQ5hv02vP7LxSQs84cTN+x/pTbz9BHT1d9Cx4dhQ8NofA11tQcGrIHNdvblUgK5xCN4QGyNrfEJXx7Njo3GqG5/g2GiMbKoTnKKdClvvTlLwKkhpV7/0KkDXOARv4o2RNT6hq+PZsdE41Y1PcGw0RjbVCQreVNh6d5KCV0FK/dKbTxLkLOfVCDg2HBt9GhsK3nzGc+2tdEXwjgb2Bi4CDgZOXQ3s5s2blz7xk2vXzv2P4vPmMp90yVnOfbqJO54dz6sRUPDmMzZqb6ULgnc74HBgP2Bn4HhgdwVvsUPLm8t8+MtZzkrpfMZAnzgreIsdM7W03gXBy1OP5wInFGinA3sA568E0QrefIaW4iHnPt0QHc+O5z6NZwVvPuO59la6IHgvAU4ETiowPwgcApyp4C1ueHlDnA97Ocu5T+LheJ7PeFbw5sO59la6KHgnAwcBZ23ZsuWIpaWlP3qv2Xbbbfe73/zmNxerHbzxSUACEpCABNogsMMOO/zq4Q9/+GXauLbX7A6BLgje04HzgOMK1jOA3YALVqvgbdq0qQv9+kP4mVY25vZ/aeTcPuO0IGc5r0bAseHYmA8BWwmBLojQrYGjgH2AXYBjgT39AlnsAPaLej785Sxnv+vmMwbkvFjOtj57Al0QvN8XBYB9gQuBA4HT/GWc/WBockXFowmt6T8r5+nZNTlTzk1oTf9ZOU/PrsmZXeTcpH9+djICXRG8yXrj9NDEnNb7wS5+gRjzerM+2flynozTej8l5/USnOx8OU/GyU/VR6B3gpcHLw4//PBn1Id69YiMeT7ZkrOcVyPg2HBsODbmMwZsZX4Eeid480NnSxKQgAQkIAEJSKBOAgpenXkxKglIQAISkIAEJDA1gb4K3k2AlwOXBE4p+9dODamFE28EvAN4HvDScv2aY844eQGQbeN+BzwW+DBQc8yXLtvaZXu7HEcU5jXHPBpqlwO+Ul7onZd81xzzLYC8m/I7Jfj/AB5aecwJdf8yJjK2HwO8p/KY8+7PxDk6dgJ2ALLxdq3fdduVHYh2BPJOtud04HfwEuWVXH8N/AL4R+DsBY2NewOvLK8Fy+vBcqz2XTDxfu0t3M+8ZKUE+ip4HwI2AZ8G3ly+ZPIFXsORL733AfmF/cKY4NUc812BhwB/D1wXeAtwU6DmmPPleLNyE/8L4CPAhspjHo3P5wJ3ALKWNIJXM+e9gPuUl4+P/37VHPNVgYjoLYHLlqf0H1Q553G2+Qvis4CM8Zo55/sir7fKmw/CPN/Htf8ORvzzxoYHlz3PnwLcYwGcbwUcAFwHeES5X2QMrJTvnzfZr72Gm6AxzIdAHwUvAhV5yhdJjtx88kX++Pkg3WYr2WXjUiWeHxTBqz3m3AQT40+BUXUpfGvmPJ6I2wLPBu7YgZhvDDwVOAf4xNhfBmodz3cvld0njAGvfTz/Q/lO6FLM4+P5bcDTgK9WPp4j/9lWcmOpNL4JuE3lMefF+t8q1f8wzz7oi/iuy/dsxC1bcx5amK32e5WX/k+8X/s271B+oDcE+ih4Vy9Vj+x2kSMvRc6XzP0qy1pu4iPB60rMQfjkInmZsk11qXbOmeq8InDnMo1Yc8z5fXx3+Zt7vtQjeKdWzvkB5QaUqfuLA08s4lEz54hdqrrXAP4UyE09f1mpOebR19f1y9KO/YAufG+8Ach051WAiHV+H2vmnKpoqniJNbMUnwFuCLx+Qd9144K3Wr7zF++J92uv7D5oOC0SGILgpXqT9Sv3b5HjNJdeS/BqjflhwN+VKYt8YY9/Udcac3KTCu7xwN6Vx5y1a+Ga9TR5ufdKglcb51QcIx1vLeuD3gXsAbxz7IZYW8wRvFRz7wb8eVlPmh1zujCes27348DbVxC82jhHQvMX63z3/iVwUvkdzBgZ/cWwtpgzw5K1ghnD+ctV+pC/HI4L3jxjXkvwRnGcv0zw/rBf+zQ3Js/pD4E+Cl4WyZ4FZBFyjvxtLAvBx6djasjguOB1IeZ8SefLOoL3K6D2mG8O/KhMdSbfp5ebetZe1To2srYxlaVUw/LvTL1kLVBuLrXGvPx36bNApm0jIbXG/MCytikP3uT4LyDrTD9Vccwjzl8u8pGxUfvv4D+XymgeFMjxOeAuZf1jrWNjfDznIb2vAX+1wHvKuOCtlu8I3sT7tddw8zOG+RDoo+CF3PuBZ5abTJ5WzXRiflFqOsYFr/aYM5WVdT+3B345BrFmzo8sU0NZqJz48zT1tYD3dmBsBPGogpeqUs2cw/dKQB4MSZXmo2XNUs2c/6w8KJQHWa5chCMPD+Xhp5q/NxLrJ4E8ZDE6ah4bqfhnevZRZYx8voyNPPBWK+fdy1+qDi5P0GYdYR4wWxTnccFb7T6Rp30n3q+9ppugsbRLoK+Cly/ATMnlYYY8Pfm4djE2uvouwKvL2p+LgB+XdYKZKqo15qy7y6tRvjfW0zzllSpTrTEn93l9RNbRZNolT8NlaqjmsTE+kMYFr+aYs77xtWWqM/EfDnygA5wjpnm6M+sG85etTB/WzDls88qfFwKRjtFRc8z5HTyu/AUr/52/BOQv3DXHnPHwOuAGwLfLrEW+o+cdc56cfXR5OCVxpHJ7rzXimHi/9kZ3Kz/caQJ9FbxOJ8XgJSABCUhAAhKQwHoIKHjroee5EpCABCQgAQlIoEICCl6FSTEkCUhAAhKQgAQksB4CCt566HmuBCQgAQlIQAISqJCAgldhUgxJAhKQgAQkIAEJrIeAgrceep4rAQlIQAISkIAEKiSg4FWYFEOSgAQkIAEJSEAC6yGg4K2HnudKQAISkIAEJCCBCgkoeBUmxZDWRSD7t96mXCFbfv1P2dv1xeu66vpO/nvgTOALDS6TF6tmP9erAXmpdF50up5jPIa82Dc7CVymbDs3zXWz9d+/AdkmaRbHnmXnmez7mV0w1htvdtfIC2qfWPK/Wow7lJfZHtugE5ctW99lR4a85Dnbso3iHr9MdiG4fNlarMHlG3/0nmWnmezvmtxmR5H8928bX8kTJCCB3hBQ8HqTSjtSCETwsjVZthfaDsgb4SMLkb7sQ7uI4xtAdgN5TYPGI1B583+21fpug/NW++h4DNl9ItteRX6Xprj2dcrenNnJ5JtTnL/SKdnpYMfS12yHNx7vNEI6qeA9HNhU9qadtCvZrSP72F6z7CywmuBdveyikn1C2zzGBS/CfQbwoLJjTpvtem0JSKBiAgpexckxtKkIRPByc79xOfsmpXKW/TCzrdqLgHsA2b8xVZtI1JFlO7v8+d+WLaFuC/xr2bLoi0UU8+99ys9TJflsEcn/Llvi/apUtPYDTi3tfKbsv5lwInnZUmh0RECzIft9gcsBHwMOKdWX7P07OrK9XfbxzJFt11KZeUO57vVLFSl77+Z66d+9y+dSXUq/z1oWQzYtH1Xw8h2wEpPs0/rhssVbYkq1L9KZqlTka3Skuph/sh1gqmGpUmYP0i+NfSb7eobl9iWO08u2cXcHDgWeBdyt9D+VsGzHtaGcH2ajeEef/SGwsWxePz5IdgVeVcQrFduI2KiCl22fEv9VgYyR+wN3GpOgC0t8K/FbLsGpxiav9yvbDEbwMo72B7JBfWI+obAaVfAyxh5f+ppt875f+pC8Jp/pc/4SknxmK8MwyxGuOe/ShVl+HgF+KPDsIugZK6Nxk7gyjrIN4t9M9RvkSRKQQC8IKHi9SKOdGCMwErxsch4xyE09MrM3cPuy/2j29LxWuUlnKis3+mzWHdmK5GXP3UhbZCY3638vArZv+fnziqi9qUhVhC6fjRTmnyuU/89NNz+PEOSGHPkYnzZLbFvK9F6qaScXkYv4RAISd6TpR8sqbbl5fxXIxuiRikyVpn+RhrSZ/4/k5nr5+bnLYkifRoKXdrIn63ImEYqIS/qYKlckIrKcqlT2cU0bqeT9APgJEMGMmPyfUhl8yVhOblimNG8JRMJy/rVL38IkvCJIo0rY2SvEm/wcXaZv3w5kevQ+y0b+p0u/IzYPKPmM4EXakrOPln1yk9vIfapwrwRuXSpxkauV+IXj6Iggps/pbyRyNLWcPVYjkWkr7afyGmYjwRtVIR9TmEaEP1T6kHymz7cr131aiScVzbSdcZu/XEQGX1Dk8VtlX9cIfPZ7zV9aMpYjeMltxlb+0pBlCh4SkMAACSh4A0x6z7s8vgZv1NXciHNDzhRtJONn5Q8yLZjqyFXKTTHr3SJJo5t2pr5y4x4dqe69D/h5qZBkY/ILgD8vIpebf6ptOX5TpCUiFKF44ApTtLl5R+BuVs55aZlayxqvVJ8inJGfUbyjOCIEx5TYIwHZjDyfT9XoZcBNS/sRqwcXsRmPYXzKM5KxEpMISIRrxGB0TpilchXpzRRt2o5spu+p+IVPRC9VpvHjO4VxJCZ5iIBEjN9SqlcRk5HgZYpxpXjDKtW7xBwBjZiNjlQ2fw1ELCM9f1pEPYIXuYtApkqYKmu4pLqZafxXlHxHVnP9lfhFAkdHRDjVyWz8HtFcPlZSGcxUfOT7n1YQvIj3T8t4SZ7Th+Qz4vbYsevlLxOpokbG8/kcqdC+q/TxI2XpQfilmhkRHwleqnwZ8yNePf+Vt3sSkMBKBBQ8x0XfCETwUj3JtGeqF18vFab0M2KQtWcjCRv1ffkar1RMcgMd3cQjNZmijDilCrRc/HKd5QvqIxLPByJtkwpeZDCVp1RetiV4IyGIZKVCF5GJ7OXmnp+l0pYHMyIx6ctqgvfuVZgsf+gh69QinOEQtiPByxq8TL1mWnivwibtpaI0fryxyFUkORXT9C9Tx08vgptrbEvwRg+F5CGMiNIeawhexkDWvoVLBDQPrNylVP5SoU2/I7/jghcRXIlfPjM6MvWfatpywUt/00byF8GNbGU6fnkFb6U+RPBSnQzj9OlTpaob8X5G6etI8hLHaHxmbWkEL/l4/QqCF+lO9ddDAhIYIAEFb4BJ73mXl6/BG+9upuQic7lBRigiF5l+jJyMP1WaP8uU6QeKIOSGnepeqjL5+fuBw4rwRBaetIbgZW1V1qylmpM1U1n7NzpGU7Sp1qQSFklMdSs37pFQrVbBSxxZDxihiASkMhZhybRl1q9FoDJlmDVcb10WQ3426m8+txKTVDXHHx4YF7zEFyYRpnOKyIRlpqJTOQqnPAU8fkScIjyRmVSWMi2ctXc5Um3L+rNRe6mQjTMbjzfivJLg5TqpAkbgMy0dFokpgpeHVDIVnPV94ZnYI3jJ+8tLBSzilnVyK/Ebf8J2tSnaMM4awUyXZpo+Vd1Uf9cjeKmCRpZTZU61cFShzfjLeDmxVCuzrCDS7BRtz7/c7J4EmhBQ8JrQ8rNdILCW4KUyNnqgIIvqc+OOeK30lGYkIRW4ncrapwhKpi1zI02lJ2vIPlfW1kVsVqvgZY1bKod5ECHCkTV3oyML8lMVyzq6VAlzjUhCpom3JXhvLmviUq3LDT4SdHPg/xbJidikWpb1fKlYZupyFEOm+kaCl2nmlZisVcFLdTAL+SNqkby/K9O2kZmvlKnGiMn4cYPyZxGVVL9GU52pQEUYx9uLwIwzG493LcHLdGdELnmOWEcgwz/SeVLhk+nTCGQqZslpWOdnmd5NX/LwSiRxnF/Wc2baeHQk33mIJtOxqVom1shr1llmjWXE/XXLxsTyMTYuqatV8PKZ/OUhf5kI2/QhfyHJXxKy5CBCmlfBZK1fPpf+p/qXKnPi8CGLLnxjGaMEWiKg4LUE1stKoEUC40LQYjNeehUCke/Iel6TUtsU6PWKjGZqfnztoMmUgAQGRkDBG1jC7W4vCCh4i01jKoRZ35gK20GLDWWr1lMhzRPieVrZFx1XlhzDkcA8CSh486RtWxKQgAQkIAEJSGAOBBS8OUC2CQlIQAISkIAEJDBPAgrePGnblgQkIAEJ3SEJwwAAAENJREFUSEACEpgDAQVvDpBtQgISkIAEJCABCcyTgII3T9q2JQEJSEACEpCABOZAQMGbA2SbkIAEJCABCUhAAvMk8P8At+QSqneKhiIAAAAASUVORK5CYII="
     },
     "metadata": {
      "jupyter-vega3": "#0fba70ad-406c-4f8e-be3a-c75b876578d1"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df[['data completion']].vgplot.hist(bins=10,\n",
    "                                    var_name='Number of hospitals',\n",
    "                                    value_name='Percent of patients with data')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The treatment table is fairly frequently used in eICU-CRD, with the majority of hospitals having some form of data in it. Of course, this is not a guarantee that the table contains reliable treatment documentation for all treatments performed during the patient's stay."
   ]
  }
 ],
 "metadata": {
  "front-matter": {
   "date": "2015-09-01",
   "linktitle": "admissiondrug",
   "title": "admissiondrug"
  },
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.5.2"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
